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Welcome to GNSS-SDR!

Visit gnss-sdr.org for more information about this open source GNSS software defined receiver.

If you have questions about GNSS-SDR, please subscribe to the gnss-sdr-developers mailing list and post your questions there.

How to build GNSS-SDR

This section describes how to set up the compilation environment in GNU/Linux or macOS / Mac OS X, and to build GNSS-SDR. See also our build and install page.

GNU/Linux

  • Tested distributions: Ubuntu 14.04 LTS and above, Debian 8.0 "jessie" and above, Linaro 15.03
  • Known to work but not continually tested: Arch Linux, Fedora, and openSUSE
  • Supported microprocessor architectures:
    • i386: Intel x86 instruction set (32-bit microprocessors).
    • amd64: also known as x86-64, the 64-bit version of the x86 instruction set, originally created by AMD and implemented by AMD, Intel, VIA and others.
    • armel: ARM embedded ABI, supported on ARM v4t and higher.
    • armhf: ARM hard float, ARMv7 + VFP3-D16 floating-point hardware extension + Thumb-2 instruction set and above.
    • arm64: ARM 64 bits or ARMv8.
    • mips: MIPS architecture (big-endian, such as those manufactured by SGI).
    • mipsel: MIPS architecture (little-endian, such as Loongson 3).
    • mips64el: 64-bit version of MIPS architecture.
    • powerpc: the RISC 32-bit microprocessor architecture developed by IBM, Motorola (now Freescale) and Apple.
    • ppc64: 64-bit big-endian PowerPC architecture.
    • ppc64el: 64-bit little-endian PowerPC architecture.
    • s390x: IBM System z architecture for mainframe computers.

Older distribution releases might work as well, but you will need GCC 4.7 or newer.

Before building GNSS-SDR, you need to install all the required dependencies. There are two alternatives here: through software packages or building them from the source code. It is in general not a good idea to mix both approaches.

Alternative 1: Install dependencies using software packages

If you want to start building and running GNSS-SDR as quick and easy as possible, the best option is to install all the required dependencies as binary packages. If you are using Debian 8, Ubuntu 14.10 or above, this can be done by copying and pasting the following line in a terminal:

$ sudo apt-get install build-essential cmake git libboost-dev libboost-date-time-dev \
       libboost-system-dev libboost-filesystem-dev libboost-thread-dev libboost-chrono-dev \
       libboost-serialization-dev libboost-program-options-dev libboost-test-dev \
       liblog4cpp5-dev libuhd-dev gnuradio-dev gr-osmosdr libblas-dev liblapack-dev \
       libarmadillo-dev libgflags-dev libgoogle-glog-dev libgnutls-openssl-dev libgtest-dev \
       python-mako python-six

Alternatively, and starting from Ubuntu 16.04 LTS, you can install all the required dependencies by adding the line

deb-src http://us.archive.ubuntu.com/ubuntu/ xenial universe

to your /etc/apt/sources.list file and doing:

$ sudo apt-get update
$ sudo apt-get build-dep gnss-sdr

Once you have installed these packages, you can jump directly to how to download the source code and build GNSS-SDR.

Note for Ubuntu 14.04 LTS "trusty" users: you will need to build from source and install GNU Radio manually, as explained below, since GNSS-SDR requires gnuradio-dev >= 3.7.3, and Ubuntu 14.04 came with 3.7.2. Install all the packages above BUT EXCEPT libuhd-dev, gnuradio-dev and gr-osmosdr (and remove them if they are already installed in your machine), and install those dependencies using PyBOMBS.

Alternative 2: Install dependencies using PyBOMBS

This option is adequate if you are interested in development, in working with the most recent versions of software dependencies, want more fine tuning on the installed versions, or simply in building everything from the scratch just for the fun of it. In such cases, we recommend to use PyBOMBS (Python Build Overlay Managed Bundle System), GNU Radio's meta-package manager tool that installs software from source, or whatever the local package manager is, that automatically does all the work for you. Please take a look at the configuration options and general PyBOMBS usage at https://github.com/gnuradio/pybombs. Here we provide a quick step-by-step tutorial.

First of all, install some basic packages:

$ sudo apt-get install git python-pip

Download, build and install PyBOMBS:

$ sudo pip install git+https://github.com/gnuradio/pybombs.git

Add some software recipes (i.e., instructions on how to install software dependencies):

$ pybombs recipes add gr-recipes git+https://github.com/gnuradio/gr-recipes.git
$ pybombs recipes add gr-etcetera git+https://github.com/gnuradio/gr-etcetera.git

Download, build and install GNU Radio, related drivers and some other extra modules into the directory /path/to/prefix (replace this path by your preferred one, for instance $HOME/sdr):

$ pybombs prefix init /path/to/prefix -a myprefix -R gnuradio-default

This will perform a local installation of the dependencies under /path/to/prefix, so they will not be visible when opening a new terminal. In order to make them available, you will need to set up the adequate environment variables:

$ cd /path/to/prefix
$ . ./setup_env.sh

Now you are ready to use GNU Radio and to jump into building GNSS-SDR after installing a few other dependencies. Actually, those are steps that PyBOMBS can do for you as well:

$ pybombs install gnss-sdr

By default, PyBOMBS installs the ‘next’ branch of GNSS-SDR development, which is the most recent version of the source code. This behaviour can be modified by altering the corresponding recipe at $HOME/.pybombs/recipes/gr-recipes/gnss-sdr.lwr

In case you do not want to use PyBOMBS and prefer to build and install GNSS-SDR step by step (i.e., cloning the repository and doing the usual cmake .. && make && make install dance), Armadillo, GFlags, Glog and GunTLS can be installed either by using PyBOMBS:

$ pybombs install armadillo gflags glog gnutls

or manually as explained below, and then please follow instructions on how to download the source code and build GNSS-SDR.

Manual installation of other required dependencies

Install Armadillo, a C++ linear algebra library:

$ sudo apt-get install libopenblas-dev liblapack-dev   # For Debian/Ubuntu/LinuxMint
$ sudo yum install lapack-devel blas-devel             # For Fedora/CentOS/RHEL
$ sudo zypper install lapack-devel blas-devel          # For OpenSUSE
$ wget http://sourceforge.net/projects/arma/files/armadillo-7.600.2.tar.xz
$ tar xvfz armadillo-7.600.2.tar.xz
$ cd armadillo-7.600.2
$ cmake .
$ make
$ sudo make install

The full stop separated from cmake by a space is important. CMake will figure out what other libraries are currently installed and will modify Armadillo's configuration correspondingly. CMake will also generate a run-time armadillo library, which is a combined alias for all the relevant libraries present on your system (eg. BLAS, LAPACK and ATLAS).

Install Gflags, a commandline flags processing module for C++:

$ wget https://github.com/gflags/gflags/archive/v2.2.0.tar.gz
$ tar xvfz v2.2.0.tar.gz
$ cd gflags-2.2.0
$ cmake -DBUILD_SHARED_LIBS=ON -DBUILD_STATIC_LIBS=OFF -DBUILD_gflags_nothreads_LIB=OFF .
$ make
$ sudo make install
$ sudo ldconfig

Install Glog, a library that implements application-level logging:

$ wget https://github.com/google/glog/archive/v0.3.4.tar.gz
$ tar xvfz v0.3.4.tar.gz
$ cd glog-0.3.4
$ ./configure
$ make
$ sudo make install
$ sudo ldconfig

Build the Google C++ Testing Framework, also known as Google Test:

$ wget https://github.com/google/googletest/archive/release-1.8.0.zip
$ unzip release-1.8.0.zip
$ cd googletest-release-1.8.0
$ cmake -DBUILD_GTEST=ON -DBUILD_GMOCK=OFF .
$ make

Please DO NOT install Google Test (do not type sudo make install). Every user needs to compile his tests using the same compiler flags used to compile the installed Google Test libraries; otherwise he may run into undefined behaviors (i.e. the tests can behave strangely and may even crash for no obvious reasons). The reason is that C++ has this thing called the One-Definition Rule: if two C++ source files contain different definitions of the same class/function/variable, and you link them together, you violate the rule. The linker may or may not catch the error (in many cases it is not required by the C++ standard to catch the violation). If it does not, you get strange run-time behaviors that are unexpected and hard to debug. If you compile Google Test and your test code using different compiler flags, they may see different definitions of the same class/function/variable (e.g. due to the use of #if in Google Test). Therefore, for your sanity, we recommend to avoid installing pre-compiled Google Test libraries. Instead, each project should compile Google Test itself such that it can be sure that the same flags are used for both Google Test and the tests. The building system of GNSS-SDR does the compilation and linking of googletest to its own tests; it is only required that you tell the system where the googletest folder that you downloaded resides. Just add to your $HOME/.bashrc file the following line:

export GTEST_DIR=/home/username/googletest-release-1.8.0/googletest

changing /home/username/googletest-release-1.8.0/googletest by the actual directory where you built googletest.

Install the GnuTLS library:

$ sudo apt-get install libgnutls-openssl-dev    # For Debian/Ubuntu/LinuxMint
$ sudo yum install libgnutls-openssl-devel      # For Fedora/CentOS/RHEL

In case the GnuTLS library with openssl extensions package is not available in your GNU/Linux distribution, GNSS-SDR can also work well with OpenSSL.

Clone GNSS-SDR's Git repository:

$ git clone https://github.com/gnss-sdr/gnss-sdr

Cloning the GNSS-SDR repository as in the line above will create a folder named gnss-sdr with the following structure:

 |-gnss-sdr
 |---build      <- where gnss-sdr is built.
 |---cmake      <- CMake-related files.
 |---conf       <- Configuration files. Each file defines one particular receiver.
 |---data       <- Populate this folder with your captured data.
 |---docs       <- Contains documentation-related files.
 |---install    <- Executables will be placed here.
 |---src        <- Source code folder.
 |-----algorithms  <- Signal processing blocks.
 |-----core     <- Control plane, interfaces, systems' parameters.
 |-----main     <- Main function of the C++ program.
 |-----tests    <- QA code.
 |-----utils    <- some utilities (e.g. Matlab scripts).

By default, you will be in the 'master' branch of the Git repository, which corresponds to the lastest stable release. If you want to try the latest developments, you can use the 'next' branch by going to the newly created gnss-sdr folder doing:

$ git checkout next

More information about GNSS-SDR-specific Git usage and pointers to further readings can be found at our Git tutorial.

Build and install GNSS-SDR

Go to GNSS-SDR's build directory:

$ cd gnss-sdr/build

Configure and build the application:

$ cmake ../
$ make

By default, CMake will build the Release version, meaning that the compiler will generate a fast, optimized executable. This is the recommended build type when using a RF front-end and you need to attain real time. If working with a file (and thus without real-time constraints), you may want to obtain more information about the internals of the receiver, as well as more fine-grained logging. This can be done by building the Debug version, by doing:

$ cmake -DCMAKE_BUILD_TYPE=Debug ../
$ make

This will create four executables at gnss-sdr/install, namely gnss-sdr, run_tests, front-end-cal and volk_gnsssdr_profile. You can run them from that folder, but if you prefer to install gnss-sdr on your system and have it available anywhere else, do:

$ sudo make install

This will also make a copy of the conf/ folder into /usr/local/share/gnss-sdr/conf for your reference. We suggest to create a working directory at your preferred location and store your own configuration and data files there.

You could be interested in creating the documentation by doing:

$ make doc

from the gnss-sdr/build folder. This will generate HTML documentation that can be retrieved pointing your browser of preference to build/docs/html/index.html. If a LaTeX installation is detected in your system,

$ make pdfmanual

will create a PDF manual at build/docs/GNSS-SDR_manual.pdf. Finally,

$ make doc-clean

will remove the content of previously-generated documentation.

GNSS-SDR comes with a library which is a module of the Vector-Optimized Library of Kernels (so called VOLK_GNSSSDR) and a profiler that will build a config file for the best SIMD architecture for your processor. Run volk_gnsssdr_profile that is installed into $PREFIX/bin. This program tests all known VOLK kernels for each architecture supported by the processor. When finished, it will write to $HOME/.volk_gnsssdr/volk_gnsssdr_config the best architecture for the VOLK function. This file is read when using a function to know the best version of the function to execute. It mimics GNU Radio's VOLK library, so if you still have not run volk_profile, this is a good moment to do so.

If you are using Eclipse as your development environment, CMake can create the project for you. Type:

$ cmake -G "Eclipse CDT4 - Unix Makefiles" -DCMAKE_BUILD_TYPE=Debug -DECLIPSE_CDT4_GENERATE_SOURCE_PROJECT=TRUE -DCMAKE_ECLIPSE_VERSION=3.7 -DCMAKE_ECLIPSE_MAKE_ARGUMENTS=-j8 ../

and then import the created project file into Eclipse:

  1. Import project using Menu File -> Import.
  2. Select General -> Existing projects into workspace.
  3. Browse where your build tree is and select the root build tree directory. Keep "Copy projects into workspace" unchecked.
  4. You get a fully functional Eclipse project.
Build GN3S V2 Custom firmware and driver (OPTIONAL):

Install the GNU Radio module:

$ git clone https://github.com/gnss-sdr/gr-gn3s
$ cd gr-gn3s/build
$ cmake ../
$ make
$ sudo make install
$ sudo ldconfig

Then configure GNSS-SDR to build the GN3S_Signal_Source by:

$ cd gnss-sdr/build
$ cmake -DENABLE_GN3S=ON ../
$ make
$ sudo make install

In order to gain access to USB ports, gnss-sdr should be used as root. In addition, the driver requires access to the GN3S firmware binary file. It should be available in the same path where the application is called. GNSS-SDR comes with a pre-compiled custom GN3S firmware available at gr-gn3s/firmware/GN3S_v2/bin/gn3s_firmware.ihx. Please copy this file to the application path.

(in order to disable the GN3S_Signal_Source compilation, you can pass -DENABLE_GN3S=OFF to cmake and build GNSS-SDR again).

More info at https://github.com/gnss-sdr/gr-gn3s

Build OSMOSDR support (OPTIONAL):

Install the OsmoSDR library and GNU Radio's source block:

$ git clone git://git.osmocom.org/osmo-sdr.git
$ cd osmo-sdr/software/libosmosdr
$ mkdir build
$ cd build/
$ cmake ../
$ make
$ sudo make install
$ sudo ldconfig
$ cd ../../
$ git clone git://git.osmocom.org/gr-osmosdr
$ cd gr-osmosdr
$ mkdir build
$ cd build
$ cmake ../ -Wno-dev
$ make
$ sudo make install
$ sudo ldconfig

Then, configure GNSS-SDR to build the Osmosdr_Signal_Source by:

$ cmake -DENABLE_OSMOSDR=ON ../
$ make
$ sudo make install

(in order to disable the Osmosdr_Signal_Source compilation, you can pass DENABLE_OSMOSDR=OFF to cmake and build GNSS-SDR again).

Build OpenCL support (OPTIONAL):

In order to enable the building of blocks that use OpenCL, type:

$ cmake -DENABLE_OPENCL=ON ../
$ make
$ sudo make install
Build CUDA support (OPTIONAL):

In order to enable the building of blocks that use CUDA, NVIDIA's parallel programming model that enables graphics processing unit (GPU) acceleration for data-parallel computations, first you need to install the CUDA Toolkit from NVIDIA Developers Download page. Make sure that the SDK samples build well. Then, build GNSS-SDR by doing:

$ cmake -DENABLE_CUDA=ON ../
$ make
$ sudo make install

Of course, you will also need a GPU that supports CUDA.

Build a portable binary

In order to build an executable that not depends on the specific SIMD instruction set that is present in the processor of the compiling machine, so other users can execute it in other machines without those particular sets, use:

$ cmake -DENABLE_GENERIC_ARCH=ON ../
$ make
$ sudo make install

Using this option, all SIMD instructions are exclusively accessed via VOLK, which automatically includes versions of each function for different SIMD instruction sets, then detects at runtime which to use, or if there are none, substitutes a generic, non-SIMD implementation.

macOS and Mac OS X

macOS Sierra, Mac OS X 10.11 (El Capitan), 10.10 (Yosemite) and 10.9 (Mavericks).

If you still have not installed Xcode, do it now from the App Store (it's free). You will also need the Xcode Command Line Tools. Launch the Terminal, found in /Applications/Utilities/, and type:

$ xcode-select --install

Agree to Xcode license:

$ sudo xcodebuild -license

Software pre-requisites can be installed using either Macports or Homebrew.

####<a name"macports">Macports

First, install Macports. If you are upgrading from a previous installation, please follow the migration rules.

In a terminal, type:

$ sudo port selfupdate
$ sudo port upgrade outdated
$ sudo port install doxygen +latex
$ sudo port install gnuradio
$ sudo port install armadillo
$ sudo port install gnutls
$ sudo port install google-glog +gflags
$ sudo port install py27-mako
$ sudo port install py27-six

You also might need to activate a Python installation. The list of installed versions can be retrieved with:

$ port select list python

and you can activate a certain version (2.7 works well) by typing:

$ sudo port select --set python python27

Homebrew

Instructions for installing GNU Radio using homebrew can be found here - please ensure to install all dependencies as required.

Install Armadillo and dependencies:

$ brew tap homebrew/science
$ brew install cmake hdf5 arpack superlu
$ brew install armadillo
$ brew install glog gflags gnutls

Build GNSS-SDR

Finally, you are ready to clone the GNSS-SDR repository, configure and build the software:

$ git clone https://github.com/gnss-sdr/gnss-sdr
$ cd gnss-sdr/build
$ cmake ../
$ make

This will create three executables at gnss-sdr/install, namely gnss-sdr, run_tests and volk_gnsssdr_profile. You can install the software receiver on your system by doing:

$ sudo make install

Note, it is advisable not to run the install step in a homebrew environment.

The documentation can be built by:

$ make doc

and can be viewed doing:

$ open ./docs/html/index.html

GNSS-SDR comes with a library which is a module of the Vector-Optimized Library of Kernels (so called VOLK_GNSSSDR) and a profiler that will build a config file for the best SIMD architecture for your processor. Run volk_gnsssdr_profile that is installed into $PREFIX/bin. This program tests all known VOLK kernels for each architecture supported by the processor. When finished, it will write to $HOME/.volk_gnsssdr/volk_gnsssdr_config the best architecture for the VOLK function. This file is read when using a function to know the best version of the function to execute. It mimics GNU Radio's VOLK library, so if you still have not run volk_profile, this is a good moment to do so.

Other package managers

GNU Radio and other dependencies can also be installed using other package managers than Macports, such as Fink or Homebrew. Since the version of Python that ships with OS X is great for learning but it is not good for development, you could have another Python executable in a non-standard location. If that is the case, you need to inform GNSS-SDR's configuration system by defining the PYTHON_EXECUTABLE variable as:

cmake -DPYTHON_EXECUTABLE=/path/to/bin/python ../

In case you have installed Macports in a non-standard location, you can use:

$ cmake -DCMAKE_PREFIX_PATH=/opt/local -DUSE_MACPORTS_PYTHON=/opt/local/bin/python ../

changing /opt/local by the base directory in which your software is installed.

The CMake script will create Makefiles that download, build and link Armadillo, Gflags, Glog and Google Test on the fly at compile time if they are not detected in your machine.

Other builds

  • Snap packages: Snaps are universal Linux packages aimed to work on any distribution or device, from IoT devices to servers, desktops to mobile devices. Visit https://github.com/carlesfernandez/snapcraft-sandbox for instructions.

  • GNSS-SDR in embedded platforms: we provide a Software Development Kit (SDK) based on OpenEmbedded for cross-compiling GNSS-SDR in your desktop computer and for producing executables that can run in embedded platforms, such as a Zedboard or a Raspberry Pi 3. Visit Cross-compiling GNSS-SDR for instructions.

Updating GNSS-SDR

If you cloned or forked GNSS-SDR some time ago, it is possible that some developer has updated files at the Git repository. If you still have not done so, add the upstream repository to the list of remotes:

$ git remote add upstream https://github.com/gnss-sdr/gnss-sdr.git

and then you can update your working copy by doing:

$ git checkout master        # Switch to branch you want to update
$ git pull upstream master   # Download the newest code from our repository

or, if you want to test the latest developments:

$ git checkout next
$ git pull upstream next

Before rebuilding the source code, it is safe (and recommended) to remove the remainders of old compilations:

$ rm -rf gnss-sdr/build/*

If you are interested in contributing to the development of GNSS-SDR, please check out how to do it.

There is a more controlled way to upgrade your repository, which is to use the Git commands fetch and merge, as described in our Git Tutorial.

Getting started

  1. After building the code, you will find the gnss-sdr executable file at gnss-sdr/install. You can make it available everywhere else by sudo make install. Run the profilers volk_profile and volk_gnsssdr_profile for testing all available VOLK kernels for each architecture supported by your processor. This only has to be done once.
  2. In post-processing mode, you have to provide a captured GNSS signal file.
    1. The signal file can be easily recorded using the GNU Radio file sink in gr_complex<float> mode.
    2. You will need a GPS active antenna, a USRP and a suitable USRP daughter board to receive GPS L1 C/A signals. GNSS-SDR require to have at least 2 MHz of bandwidth in 1.57542 GHz. (remember to enable the DC bias with the daughter board jumper). We use a DBSRX2 to do the task, but you can try the newer Ettus' daughter boards as well.
    3. The easiest way to capture a signal file is to use the GNU Radio Companion GUI. Only two blocks are needed: a USRP signal source connected to complex float file sink. You need to tune the USRP central frequency and decimation factor using USRP signal source properties box. We suggest using a decimation factor of 20 if you use the USRP2. This will give you 100/20 = 5 MSPS which will be enough to receive GPS L1 C/A signals. The front-end gain should also be configured. In our test with the DBSRX2 we obtained good results with G=50.
    4. Capture at least 80 seconds of signal in open sky conditions. During the process, be aware of USRP driver buffer underuns messages. If your hard disk is not fast enough to write data at this speed you can capture to a virtual RAM drive. 80 seconds of signal at 5 MSPS occupies less than 3 Gbytes using gr_complex<float>.
    5. If you have no access to a RF front-end, you can download a sample raw data file (that contains GPS and Galileo signals) from here.
  3. You are ready to configure the receiver to use your captured file among other parameters:
    1. The default configuration file resides at /usr/local/share/gnss-sdr/conf/default.conf.
    2. You need to review/modify at least the following settings:
      • SignalSource.filename= (absolute or relative route to your GNSS signal captured file)
      • GNSS-SDR.internal_fs_hz= (captured file sampling rate in Hz)
      • SignalSource.sampling_frequency= (captured file sampling rate in Hz)
      • SignalConditioner.sample_freq_in= (captured file sampling rate in Hz)
      • SignalConditioner.sample_freq_out= (captured file sampling rate in Hz)
      • TelemetryDecoder.fs_in= (captured file sampling rate in Hz)
    3. The configuration file has in-line documentation, you can try to tune the number of channels and several receiver parameters. Store your .conf file in some working directory of your choice.
  4. Run the receiver invoking the configuration by $ gnss-sdr --config_file=/path/to/my_receiver.conf The program reports the current status in text mode, directly to the terminal window. If all goes well, and GNSS-SDR is able to successfully track and decode at least 4 satellites, you will get PVT fixes. The program will write .kml, .geojson and RINEX files in the folder from which gnss-sdr was run. In addition to the console output, GNSS-SDR also writes log files at /tmp/ (configurable with the commandline flag ./gnss-sdr --log_dir=/path/to/log).

For more information, check out our quick start guide.

Using GNSS-SDR

With GNSS-SDR, you can define you own receiver, work with captured raw data or from a RF front-end, dump into files intermediate signals, or tune every single algorithm used in the signal processing. All the configuration is done in a single file. Those configuration files reside at the gnss-sdr/conf/ folder (or at /usr/local/share/gnss-sdr/conf if you installed the program). By default, the executable gnss-sdr will read the configuration available at gnss-sdr/conf/gnss-sdr.conf (or at (usr/local/share/gnss-sdr/conf/default.conf if you installed the program). You can edit that file to fit your needs, or even better, define a new my_receiver.conf file with your own configuration. This new receiver can be generated by invoking gnss-sdr with the --config_file flag pointing to your configuration file:

$ gnss-sdr --config_file=/path/to/my_receiver.conf

You can use a single configuration file for processing different data files, specifying the file to be processed with the --signal_source flag:

$ gnss-sdr --config_file=../conf/my_receiver.conf --signal_source=../data/my_captured_data.dat

This will override the SignalSource.filename specified in the configuration file.

Control plane

GNSS-SDR's main method initializes the logging library, processes the command line flags, if any, provided by the user and instantiates a ControlThread object. Its constructor reads the configuration file, creates a control queue and creates a flowgraph according to the configuration. Then, the program's main method calls the run() method of the instantiated object, an action that connects the flowgraph and starts running it. After that, and until a stop message is received, it reads control messages sent by the receiver's modules through a safe-thread queue and processes them. Finally, when a stop message is received, the main method executes the destructor of the ControlThread object, which deallocates memory, does other cleanup and exits the program.

The GNSSFlowgraph class is responsible for preparing the graph of blocks according to the configuration, running it, modifying it during run-time and stopping it. Blocks are identified by its role. This class knows which roles it has to instantiate and how to connect them. It relies on the configuration to get the correct instances of the roles it needs and then it applies the connections between GNU Radio blocks to make the graph ready to be started. The complexity related to managing the blocks and the data stream is handled by GNU Radio's gr::top_block class. GNSSFlowgraph wraps the gr::top_block instance so we can take advantage of the gnss_block_factory (see below), the configuration system and the processing blocks. This class is also responsible for applying changes to the configuration of the flowgraph during run-time, dynamically reconfiguring channels: it selects the strategy for selecting satellites. This can range from a sequential search over all the satellites' ID to other more efficient approaches.

The Control Plane is in charge of creating a flowgraph according to the configuration and then managing the modules. Configuration allows users to define in an easy way their own custom receiver by specifying the flowgraph (type of signal source, number of channels, algorithms to be used for each channel and each module, strategies for satellite selection, type of output format, etc.). Since it is difficult to foresee what future module implementations will be needed in terms of configuration, we used a very simple approach that can be extended without a major impact in the code. This can be achieved by simply mapping the names of the variables in the modules with the names of the parameters in the configuration.

Configuration

Properties are passed around within the program using the ConfigurationInterface class. There are two implementations of this interface: FileConfiguration and InMemoryConfiguration. FileConfiguration reads the properties (pairs of property name and value) from a file and stores them internally. InMemoryConfiguration does not read from a file; it remains empty after instantiation and property values and names are set using the set property method. FileConfiguration is intended to be used in the actual GNSS-SDR application whereas InMemoryConfiguration is intended to be used in tests to avoid file-dependency in the file system. Classes that need to read configuration parameters will receive instances of ConfigurationInterface from where they will fetch the values. For instance, parameters related to SignalSource should look like this:

SignalSource.parameter1=value1
SignalSource.parameter2=value2

The name of these parameters can be anything but one reserved word: implementation. This parameter indicates in its value the name of the class that has to be instantiated by the factory for that role. For instance, if our signal source is providing data already at baseband and thus we want to use the implementation Pass_Through for module SignalConditioner, the corresponding line in the configuration file would be

SignalConditioner.implementation=Pass_Through

Since the configuration is just a set of property names and values without any meaning or syntax, the system is very versatile and easily extendable. Adding new properties to the system only implies modifications in the classes that will make use of these properties. In addition, the configuration files are not checked against any strict syntax so it is always in a correct status (as long as it contains pairs of property names and values in the INI format).

GNSS block factory

Hence, the application defines a simple accessor class to fetch the configuration pairs of values and passes them to a factory class called GNSSBlockFactory. This factory decides, according to the configuration, which class needs to be instantiated and which parameters should be passed to the constructor. Hence, the factory encapsulates the complexity of blocks' instantiation. With that approach, adding a new block that requires new parameters will be as simple as adding the block class and modifying the factory to be able to instantiate it. This loose coupling between the blocks' implementations and the syntax of the configuration enables extending the application capacities in a high degree. It also allows to produce fully customized receivers, for instance a testbed for acquisition algorithms, and to place observers at any point of the receiver chain.

More information can be found at the Control Plane page.

Signal Processing plane

GNU Radio's class gr::basic_block is the abstract base class for all signal processing blocks, a bare abstraction of an entity that has a name and a set of inputs and outputs. It is never instantiated directly; rather, this is the abstract parent class of both gr::hier_block2, which is a recursive container that adds or removes processing or hierarchical blocks to the internal graph, and gr::block, which is the abstract base class for all the processing blocks.

A signal processing flow is constructed by creating a tree of hierarchical blocks, which at any level may also contain terminal nodes that actually implement signal processing functions.

Class gr::top_block is the top-level hierarchical block representing a flowgraph. It defines GNU Radio runtime functions used during the execution of the program: run(), start(), stop(), wait(), etc. A a subclass called GNSSBlockInterface is the common interface for all the GNSS-SDR modules. It defines pure virtual methods, that are required to be implemented by a derived class.

Subclassing GNSSBlockInterface, we defined interfaces for the GNSS receiver blocks depicted in the figure above. This hierarchy provides the definition of different algorithms and different implementations, which will be instantiated according to the configuration. This strategy allows multiple implementations sharing a common interface, achieving the objective of decoupling interfaces from implementations: it defines a family of algorithms, encapsulates each one, and makes them interchangeable. Hence, we let the algorithm vary independently from the program that uses it.

Internally, GNSS-SDR makes use of the complex data types defined by VOLK. They are fundamental for handling sample streams in which samples are complex numbers with real and imaginary components of 8, 16 or 32 bits, common formats delivered by GNSS (and generic SDR) radio frequency front-ends. The following list shows the data type names that GNSS-SDR exposes through the configuration file:

  • byte: Signed integer, 8-bit two's complement number ranging from -128 to 127. C++ type name: int8_t.
  • short: Signed integer, 16-bit two's complement number ranging from -32768 to 32767. C++ type name: int16_t .
  • float: Defines numbers with fractional parts, can represent values ranging from approx. 1.5e-45 to 3.4e+38 with a precision of 7 digits (32 bits). C++ type name: float.
  • ibyte: Interleaved (I&Q) stream of samples of type byte. C++ type name: int8_t.
  • ishort: Interleaved (I&Q) stream of samples of type short. C++ type name: int16_t.
  • cbyte: Complex samples, with real and imaginary parts of type byte. C++ type name: lv_8sc_t.
  • cshort: Complex samples, with real and imaginary parts of type short. C++ type name: lv_16sc_t.
  • gr_complex: Complex samples, with real and imaginary parts of type float. C++ type name: std::complex<float>.

More information about the available processing blocks and their configuration parameters can be found at the Signal Processing Blocks documentation page.

Signal Source

The input of a software receiver are the raw bits that come out from the front-end's analog-to-digital converter (ADC). Those bits can be read from a file stored in the hard disk or directly in real-time from a hardware device through USB or Ethernet buses.

The Signal Source module is in charge of implementing the hardware driver, that is, the portion of the code that communicates with the RF front-end and receives the samples coming from the ADC. This communication is usually performed through USB or Ethernet buses. Since real-time processing requires a highly optimized implementation of the whole receiver, this module also allows to read samples from a file stored in a hard disk, and thus processing without time constraints. Relevant parameters of those samples are the intermediate frequency (or baseband I&Q components), the sampling rate and number of bits per sample, that must be specified by the user in the configuration file.

This module also performs bit-depth adaptation, since most of the existing RF front-ends provide samples quantized with 2 or 3 bits, while operations inside the processor are performed on 32- or 64-bit words, depending on its architecture. Although there are implementations of the most intensive computational processes (mainly correlation) that take advantage of specific data types and architectures for the sake of efficiency, the approach is processor-specific and hardly portable. We suggest to keep signal samples in standard data types and letting the compiler select the best library version (implemented using SIMD or any other processor-specific technology) of the required routines for a given processor.

Example: File Signal Source

The user can configure the receiver for reading from a file, setting in the configuration file the data file location, sample format, and the sampling frequency and intermediate frequency at what the signal was originally captured.

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=File_Signal_Source
SignalSource.filename=/home/user/gnss-sdr/data/my_capture.dat
SignalSource.item_type=gr_complex
SignalSource.sampling_frequency=4000000 ; Sampling frequency in [Hz]
SignalSource.freq=1575420000 ; RF front-end center frequency in [Hz]

Type gr_complex refers to a GNU Radio typedef equivalent to std::complex<float>. In order to save some storage space, you might wanted to store your signal in a more efficient format such as an I/Q interleaved ```short`` integer sample stream. In that case, change the corresponding line to:

SignalSource.item_type=short

In this latter case, you will need to convert the interleaved I/Q samples to a complex stream via Data Type Adapter block (see below).

Example: Two-bit packed file source

Sometimes, samples are stored in files with a format which is not in the list of native types supported by the File_Signal_Source implementation (i.e, it is not among byte, ibyte, short, ishort, float or gr_complex). This is the case of 2-bit samples, which is a common format delivered by GNSS RF front-ends. The Two_Bit_Packed_File_Signal_Source implementation allows reading two-bit length samples from a file. The data is assumed to be packed as bytes item_type=byte or shorts item_type=short so that there are 4 two bit samples in each byte. The two bit values are assumed to have the following interpretation:

b_1 b_0 Value
0 0 +1
0 1 +3
1 0 -3
1 1 -1

Within a byte the samples may be packed in big endian big_endian_bytes=true (if the most significant byte value is stored at the memory location with the lowest address, the next byte value in significance is stored at the following memory location, and so on) or little endian big_endian_bytes=false (if the least significant byte value is at the lowest address, and the other bytes follow in increasing order of significance). If the order is big endian then the most significant two bits will form the first sample output, otherwise the least significant two bits will be used.

Additionally the samples may be either real sample_type=real, or complex. If the sample type is complex, then the samples are either stored in the order: real, imag, real, imag, ... sample_type=iq or in the order: imag, real, imag, real, ... sample_type=qi.

Finally, if the data is stored as shorts item_type=short, then it may be stored in either big endian big_endian_items=true or little endian big_endian_items=false. If the shorts are big endian then the 2nd byte in each short is output first.

The output data type is either float or gr_complex depending on whether or not sample_type is real. Example:

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=Two_Bit_Packed_File_Signal_Source
SignalSource.filename=/data/my_capture.datz
SignalSource.item_type=short
SignalSource.sampling_frequency=60000000
SignalSource.freq=1575468750
SignalSource.samples=6000000000  ; Notice that 0 indicates the entire file.
SignalSource.repeat=false
SignalSource.dump=false
SignalSource.dump_filename=./signal_source.dat
SignalSource.enable_throttle_control=false
SignalSource.sample_type=iq
SignalSource.big_endian_items=true
SignalSource.big_endian_bytes=false

Example: UHD Signal Source

The user may prefer to use a UHD-compatible RF front-end and try real-time processing. For instance, for a USRP1 + DBSRX daughterboard, use:

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=UHD_Signal_Source
SignalSource.item_type=gr_complex
SignalSource.sampling_frequency=4000000 ; Sampling frequency in [Hz]
SignalSource.freq=1575420000 ; RF front-end center frequency in [Hz]
SignalSource.gain=60 ; Front-end gain in dB
SignalSource.subdevice=B:0 ; UHD subdevice specification (for USRP1 use A:0 or B:0, for USRP B210 use A:0)

Example: Configuring the USRP X300 with two front-ends for receiving signals in L1 and L2 bands

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=UHD_Signal_Source
SignalSource.device_address=192.168.40.2 ; Put your USRP IP address here
SignalSource.item_type=gr_complex
SignalSource.RF_channels=2
SignalSource.sampling_frequency=4000000
SignalSource.subdevice=A:0 B:0

;######### RF Channels specific settings ######
SignalSource.freq0=1575420000
SignalSource.gain0=50
SignalSource.samples0=0
SignalSource.dump0=false

SignalSource.freq1=1227600000
SignalSource.gain1=50
SignalSource.samples1=0
SignalSource.dump1=false

Example: OsmoSDR-compatible Signal Source

OsmoSDR is a small form-factor, inexpensive software defined radio project. It provides a driver for several front-ends, such as RTL-based dongles, HackRF, bladeRF, etc. Note that not all the OsmoSDR-compatible devices can work as radio frequency front-ends for proper GNSS signal reception, please check the specifications. For suitable RF front-ends, you can use:

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=Osmosdr_Signal_Source
SignalSource.item_type=gr_complex
SignalSource.sampling_frequency=2000000
SignalSource.freq=1575420000
SignalSource.rf_gain=40
SignalSource.if_gain=30
SignalSource.enable_throttle_control=false
SignalSource.osmosdr_args=rtl_tcp,offset_tune=1

In case of using a Zarlink's RTL2832 based DVB-T receiver, you can even use the rtl_tcp I/Q server in order to use the USB dongle remotely. In a terminal, type:

$ rtl_tcp -a 127.0.0.1 -p 1234 -f 1575420000 -g 0 -s 2000000

and use the following configuration:

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=RtlTcp_Signal_Source
SignalSource.item_type=gr_complex
SignalSource.sampling_frequency=1200000
SignalSource.freq=1575420000
SignalSource.gain=40
SignalSource.rf_gain=40
SignalSource.if_gain=30
SignalSource.AGC_enabled=false
SignalSource.samples=0
SignalSource.enable_throttle_control=false
SignalSource.address=127.0.0.1
SignalSource.port=1234
SignalSource.swap_iq=false
SignalSource.repeat=false
SignalSource.dump=false
SignalSource.dump_filename=../data/signal_source.dat

Example for a dual-frequency receiver:

;######### SIGNAL_SOURCE CONFIG ############
SignalSource.implementation=UHD_Signal_Source
SignalSource.device_address=192.168.40.2 ; Put your USRP IP address here
SignalSource.item_type=gr_complex
SignalSource.RF_channels=2
SignalSource.sampling_frequency=4000000
SignalSource.subdevice=A:0 B:0

;######### RF Channels specific settings ######
SignalSource.freq0=1575420000
SignalSource.gain0=50
SignalSource.samples0=0
SignalSource.dump0=false

SignalSource.freq1=1227600000
SignalSource.gain1=50
SignalSource.samples1=0
SignalSource.dump1=false

More documentation and examples are available at the Signal Source Blocks page.

Signal Conditioner

The signal conditioner is in charge of resampling the signal and delivering a reference sample rate to the downstream processing blocks, acting as a facade between the signal source and the synchronization channels, providing a simplified interface to the input signal. In case of multiband front-ends, this module would be in charge of providing a separated data stream for each band.

If your signal source is providing baseband signal samples of type gr_complex at 4 Msps, you can bypass the Signal Conditioner block by:

SignalConditioner.implementation=Pass_Through

If you need to adapt some aspect of you signal, you can enable the Signal Conditioner and configure three internal blocks: a data type adpater, an input signal and a resampler.

;#[Signal_Conditioner] enables this block. Then you have to configure [DataTypeAdapter], [InputFilter] and [Resampler] blocks
SignalConditioner.implementation=Signal_Conditioner

More documentation at the Signal Conditioner Blocks page.

Data type adapter

This block changes the type of input data samples. If your signal source delivers data samples of type short, you can use this block to convert them to gr_complex like this:

;######### DATA_TYPE_ADAPTER CONFIG ############
;#implementation: [Pass_Through] disables this block
DataTypeAdapter.implementation=Ishort_To_Complex

More documentation at the Data Type Adapter Blocks page.

Input filter

This block filters the input data. It can be combined with frequency translation for IF signals. The computation of the filter taps is based on parameters of GNU Radio's function pm_remez, that calculates the optimal (in the Chebyshev/minimax sense) FIR filter impulse response given a set of band edges, the desired reponse on those bands, and the weight given to the error in those bands.

The block can be configured like this:

;######### INPUT_FILTER CONFIG ############
;#implementation: Use [Pass_Through] or [Fir_Filter] or [Freq_Xlating_Fir_Filter]
;#[Pass_Through] disables this block
;#[Fir_Filter] enables a FIR Filter
;#[Freq_Xlating_Fir_Filter] enables FIR filter and a composite frequency translation that shifts IF down to zero Hz.
InputFilter.implementation=Freq_Xlating_Fir_Filter
InputFilter.dump=false ; #dump: Dump the filtered data to a file.
InputFilter.dump_filename=../data/input_filter.dat ; #dump_filename: Log path and filename.
InputFilter.input_item_type=gr_complex
InputFilter.output_item_type=gr_complex
InputFilter.taps_item_type=float
InputFilter.number_of_taps=5 ; #number_of_taps: Number of taps in the filter. Increasing this parameter increases the processing time
InputFilter.number_of_bands=2 ; #number_of_bands: Number of frequency bands in the filter.
; Frequency is in the range [0, 1], with 1 being the Nyquist frequency (Fs/2)
; The number of band_begin and band_end elements must match the number of bands
InputFilter.band1_begin=0.0
InputFilter.band1_end=0.85
InputFilter.band2_begin=0.90
InputFilter.band2_end=1.0

;#ampl: desired amplitude at the band edges.
;#The number of ampl_begin and ampl_end elements must match the number of bands
InputFilter.ampl1_begin=1.0
InputFilter.ampl1_end=1.0
InputFilter.ampl2_begin=0.0
InputFilter.ampl2_end=0.0

;#band_error: weighting applied to each band (usually 1).
;#The number of band_error elements must match the number of bands
InputFilter.band1_error=1.0
InputFilter.band2_error=1.0

;#filter_type: one of "bandpass", "hilbert" or "differentiator"
InputFilter.filter_type=bandpass

;#grid_density: determines how accurately the filter will be constructed.
;The minimum value is 16; higher values are slower to compute the filter.
InputFilter.grid_density=16

;#The following options are used only in Freq_Xlating_Fir_Filter implementation.
;#InputFilter.IF is the intermediate frequency (in Hz) shifted down to zero Hz
InputFilter.sampling_frequency=4000000
InputFilter.IF=0
InputFilter.decimation_factor=1

More documentation at the Input Filter Blocks page.

Resampler

This block resamples the input data stream. The Direct_Resampler block implements a nearest neigbourhood interpolation:

;######### RESAMPLER CONFIG ############
;#implementation: Use [Pass_Through] or [Direct_Resampler]
;#[Pass_Through] disables this block
Resampler.implementation=Direct_Resampler
Resampler.dump=false ; Dumps the resampled data to a file.
Resampler.dump_filename=../data/resampler.dat ; log path and filename.
Resampler.item_type=gr_complex
Resampler.sample_freq_in=8000000 ; sample frequency of the input signal
Resampler.sample_freq_out=4000000 ; desired sample frequency of the output signal

More documentation at the Resampler Blocks page.

Channel

A channel encapsulates all signal processing devoted to a single satellite. Thus, it is a large composite object which encapsulates the acquisition, tracking and navigation data decoding modules. As a composite object, it can be treated as a single entity, meaning that it can be easily replicated. Since the number of channels is selectable by the user in the configuration file, this approach helps improving the scalability and maintainability of the receiver.

Each channel must be assigned to a GNSS signal, according to the following identifiers:

Signal Identifier
GPS L1 C/A 1C
GPS L2 L2C(M) 2S
Galileo E1B 1B
Galileo E5a (I+Q) 5X

Example: Eight GPS L1 C/A channels.

;######### CHANNELS GLOBAL CONFIG ############
Channels_1C.count=8 ; Number of available GPS L1 C/A channels.
Channels_1B.count=0 ; Number of available Galileo E1B channels.
Channels.in_acquisition=1 ; Number of channels simultaneously acquiring
Channel.signal=1C ;

Example: Four GPS L1 C/A and four Galileo E1B channels.

;######### CHANNELS GLOBAL CONFIG ############
Channels_1C.count=4 ; Number of available GPS L1 C/A channels.
Channels_1B.count=4 ; Number of available Galileo E1B channels.
Channels.in_acquisition=1 ; Number of channels simultaneously acquiring
Channel0.signal=1C ;
Channel1.signal=1C ;
Channel2.signal=1C ;
Channel3.signal=1C ;
Channel4.signal=1B ;
Channel5.signal=1B ;
Channel6.signal=1B ;
Channel7.signal=1B ;

This module is also in charge of managing the interplay between acquisition and tracking. Acquisition can be initialized in several ways, depending on the prior information available (called cold start when the receiver has no information about its position nor the satellites almanac; warm start when a rough location and the approximate time of day are available, and the receiver has a recently recorded almanac broadcast; or hot start when the receiver was tracking a satellite and the signal line of sight broke for a short period of time, but the ephemeris and almanac data is still valid, or this information is provided by other means), and an acquisition process can finish deciding that the satellite is not present, that longer integration is needed in order to confirm the presence of the satellite, or declaring the satellite present. In the latter case, acquisition process should stop and trigger the tracking module with coarse estimations of the synchronization parameters. The mathematical abstraction used to design this logic is known as finite state machine (FSM), that is a behavior model composed of a finite number of states, transitions between those states, and actions. For the implementation, we use the Boost.Statechart library, which provides desirable features such as support for asynchronous state machines, multi-threading, type-safety, error handling and compile-time validation.

The abstract class ChannelInterface represents an interface to a channel GNSS block. Check Channel for an actual implementation.

More documentation at the Channels page.

Acquisition

The first task of a GNSS receiver is to detect the presence or absence of in-view satellites. This is done by the acquisition system process, which also provides a coarse estimation of two signal parameters: the frequency shift with respect to the nominal IF frequency, and a delay term which allows the receiver to create a local code aligned with the incoming code. AcquisitionInterface is the common interface for all the acquisition algorithms and their corresponding implementations. Algorithms' interface, that may vary depending on the use of information external to the receiver, such as in Assisted GNSS, is defined in classes referred to as adapters. These adapters wrap the GNU Radio blocks interface into a compatible interface expected by AcquisitionInterface. This allows the use of existing GNU Radio blocks derived from gr::block, and ensures that newly developed implementations will also be reusable in other GNU Radio-based applications. Moreover, it adds still another layer of abstraction, since each given acquisition algorithm can have different implementations (for instance using different numerical libraries). In such a way, implementations can be continuously improved without having any impact neither on the algorithm interface nor the general acquisition interface.

Check GpsL1CaPcpsAcquisition and GalileoE1PcpsAmbiguousAcquisition for examples of adapters from a Parallel Code Phase Search (PCPS) acquisition block, and pcps_acquisition_cc for an example of a block implementation. The source code of all the available acquisition algorithms is located at:

  |-gnss-sdr
  |---src
  |-----algorithms
  |-------acquisition
  |---------adapters          <- Adapters of the processing blocks to an AcquisitionInterface
  |---------gnuradio_blocks   <- Signal processing blocks implementation

The user can select a given implementation for the algorithm to be used in each receiver channel, as well as their parameters, in the configuration file. For a GPS l1 C/A receiver:

;######### ACQUISITION GLOBAL CONFIG ############
Acquisition_1C.implementation=GPS_L1_CA_PCPS_Acquisition ; Acquisition algorithm selection for this channel
Acquisition_1C.item_type=gr_complex
Acquisition_1C.if=0 ; Signal intermediate frequency in [Hz]
Acquisition_1C.sampled_ms=1 ; Signal block duration for the acquisition signal detection [ms]
Acquisition_1C.threshold=0.005 ; Acquisition threshold
Acquisition_1C.pfa=0.0001 ; Acquisition false alarm probability. This option overrides the threshold option.
;                        Only use with implementations: [GPS_L1_CA_PCPS_Acquisition] or [Galileo_E1_PCPS_Ambiguous_Acquisition]
Acquisition_1C.doppler_max=10000 ; Maximum expected Doppler shift [Hz]
Acquisition_1C.doppler_step=500 ; Doppler step in the grid search [Hz]
Acquisition_1C.dump=false ; Enables internal data file logging [true] or [false]
Acquisition_1C.dump_filename=./acq_dump.dat ; Log path and filename

and, for Galileo E1B channels:

;######### GALILEO ACQUISITION CONFIG ############
Acquisition_1B.implementation=Galileo_E1_PCPS_Ambiguous_Acquisition
Acquisition_1B.item_type=gr_complex
Acquisition_1B.if=0
Acquisition_1B.sampled_ms=4
Acquisition_1B.pfa=0.0000008
Acquisition_1B.doppler_max=15000
Acquisition_1B.doppler_step=125
Acquisition_1B.dump=false
Acquisition_1B.dump_filename=./acq_dump.dat

More documentation at the Acquisition Blocks page.

Tracking

When a satellite is declared present, the parameters estimated by the acquisition module are then fed to the receiver tracking module, which represents the second stage of the signal processing unit, aiming to perform a local search for accurate estimates of code delay and carrier phase, and following their eventual variations.

Again, a class hierarchy consisting of a TrackingInterface class and subclasses implementing algorithms provides a way of testing different approaches, with full access to their parameters. Check GpsL1CaDllPllTracking or GalileoE1DllPllVemlTracking for examples of adapters, and Gps_L1_Ca_Dll_Pll_Tracking_cc for an example of a signal processing block implementation. There are also available some useful classes and functions for signal tracking; take a look at cpu_multicorrelator.h, lock_detectors.h, tracking_discriminators.h or tracking_2nd_DLL_filter.h.

The source code of all the available tracking algorithms is located at:

  |-gnss-sdr
  |---src
  |-----algorithms
  |-------tracking
  |---------adapters          <- Adapters of the processing blocks to a TrackingInterface
  |---------gnuradio_blocks   <- Signal processing blocks implementation
  |---------libs              <- libraries of tracking objects (e.g. correlators, discriminators, and so on)

The user can select a given implementation for the algorithm to be used in all the tracking blocks, as well as its parameters, in the configuration file. For instance, for GPS l1 channels:

;######### TRACKING GPS L1 CONFIG ############
Tracking_1C.implementation=GPS_L1_CA_DLL_PLL_Tracking
Tracking_1C.item_type=gr_complex
Tracking_1C.pll_bw_hz=50.0 ; PLL loop filter bandwidth [Hz]
Tracking_1C.dll_bw_hz=2.0 ; DLL loop filter bandwidth [Hz]
Tracking_1C.order=3 ; PLL/DLL loop filter order [2] or [3]
Tracking_1C.early_late_space_chips=0.5 ; correlator early-late space [chips].
Tracking_1C.dump=false ; Enable internal binary data file logging [true] or [false]
Tracking_1C.dump_filename=./tracking_ch_ ; Log path and filename. Notice that the tracking channel will add "x.dat" where x is the channel number.

and, for Galileo E1B channels:

;######### TRACKING GALILEO E1B CONFIG ############
Tracking_1B.implementation=Galileo_E1_DLL_PLL_VEML_Tracking
Tracking_1B.item_type=gr_complex
Tracking_1B.pll_bw_hz=15.0;
Tracking_1B.dll_bw_hz=2.0;
Tracking_1B.order=3;
Tracking_1B.early_late_space_chips=0.15;
Tracking_1B.very_early_late_space_chips=0.6;
Tracking_1B.dump=false
Tracking_1B.dump_filename=../data/veml_tracking_ch_

More documentation at the Tracking Blocks page.

Decoding of the navigation message

Most of GNSS signal links are modulated by a navigation message containing the time the message was transmitted, orbital parameters of satellites (also known as ephemeris) and an almanac (information about the general system health, rough orbits of all satellites in the network as well as data related to error correction). Navigation data bits are structured in words, pages, subframes, frames and superframes. Sometimes, bits corresponding to a single parameter are spread over different words, and values extracted from different frames are required for proper decoding. Some words are for synchronization purposes, others for error control an others contain actual information. There are also error control mechanisms, from parity checks to forward error correction (FEC) encoding and interleaving, depending on the system. All this decoding complexity is managed by a finite state machine implemented with the Boost.Statechart library.

The common interface is TelemetryDecoderInterface. Check GpsL1CaTelemetryDecoder for an example of the GPS L1 NAV message decoding adapter, and gps_l1_ca_telemetry_decoder_cc for an actual implementation of a signal processing block. Configuration example:

;######### TELEMETRY DECODER CONFIG ############
TelemetryDecoder_1C.implementation=GPS_L1_CA_Telemetry_Decoder
TelemetryDecoder_1C.dump=false

In case you are configuring a multi-system receiver, you will need to decimate the one with the fastest code rate in order to get both data streams synchronized. For instance, for hybrid GPS L1 / Galileo E1B receivers:

;######### TELEMETRY DECODER GPS L1 CONFIG ############
TelemetryDecoder_1C.implementation=GPS_L1_CA_Telemetry_Decoder
TelemetryDecoder_1C.dump=false
TelemetryDecoder_1C.decimation_factor=4;

;######### TELEMETRY DECODER GALILEO E1B CONFIG ############
TelemetryDecoder_1B.implementation=Galileo_E1B_Telemetry_Decoder
TelemetryDecoder_1B.dump=false
TelemetryDecoder_1B.decimation_factor=1;

More documentation at the Telemetry Decoder Blocks page.

Observables

GNSS systems provide different kinds of observations. The most commonly used are the code observations, also called pseudoranges. The pseudo comes from the fact that on the receiver side the clock error is unknown and thus the measurement is not a pure range observation. High accuracy applications also use the carrier phase observations, which are based on measuring the difference between the carrier phase transmitted by the GNSS satellites and the phase of the carrier generated in the receiver. Both observables are computed from the outputs of the tracking module and the decoding of the navigation message. This module collects all the data provided by every tracked channel, aligns all received data into a coherent set, and computes the observables.

The common interface is ObservablesInterface.

Configuration example for GPS L1 C/A signals:

;######### OBSERVABLES CONFIG ############
Observables.implementation=GPS_L1_CA_Observables
Observables.dump=false
Observables.dump_filename=./observables.dat

For Galileo E1B receivers:

;######### OBSERVABLES CONFIG ############
Observables.implementation=Galileo_E1B_Observables
Observables.dump=false
Observables.dump_filename=./observables.dat

For hybrid GPS L1 / Galileo E1B receivers:

;######### OBSERVABLES CONFIG ############
Observables.implementation=Hybrid_Observables
Observables.dump=false
Observables.dump_filename=./observables.dat

More documentation at the Observables Blocks page.

Computation of Position, Velocity and Time

Although data processing for obtaining high-accuracy PVT solutions is out of the scope of GNSS-SDR, we provide a module that can compute simple least square solutions (stored in GIS-friendly formats such as GeoJSON and KML, or transmitted via serial port as NMEA 0183 messages), and leaves room for more sophisticated positioning methods by storing observables and navigation data in RINEX files (v2.11 or v3.02), and generating RTCM 3.2 messages that can be disseminated through the Internet in real time.

The common interface is PvtInterface.

Configuration example for GPS L1 C/A signals:

;######### PVT CONFIG ############
PVT.implementation=GPS_L1_CA_PVT
PVT.averaging_depth=10 ; Number of PVT observations in the moving average algorithm
PVT.flag_averaging=true ; Enables the PVT averaging between output intervals (arithmetic mean) [true] or [false]
PVT.output_rate_ms=100 ; Period in [ms] between two PVT outputs
PVT.display_rate_ms=500 ; Position console print (std::out) interval [ms].
PVT.dump=false ; Enables the PVT internal binary data file logging [true] or [false]
PVT.dump_filename=./PVT ; Log path and filename without extension of GeoJSON and KML files
PVT.nmea_dump_filename=./gnss_sdr_pvt.nmea ; NMEA log path and filename
PVT.flag_nmea_tty_port=true ; Enables the NMEA log to a serial TTY port
PVT.nmea_dump_devname=/dev/pts/4 ; serial device descriptor for NMEA logging
PVT.flag_rtcm_server=false ; Enables or disables a TCP/IP server dispatching RTCM messages
PVT.flag_rtcm_tty_port=true ; Enables the RTCM log to a serial TTY port
PVT.rtcm_dump_devname=/dev/pts/1 ; serial device descriptor for RTCM logging

For Galileo E1B receivers:

;######### PVT CONFIG ############
PVT.implementation=GALILEO_E1_PVT
PVT.averaging_depth=100
PVT.flag_averaging=false
PVT.output_rate_ms=100;
PVT.display_rate_ms=500;
PVT.dump=false
PVT.dump_filename=./PVT
PVT.nmea_dump_filename=./gnss_sdr_pvt.nmea ; NMEA log path and filename
PVT.flag_nmea_tty_port=true ; Enables the NMEA log to a serial TTY port
PVT.nmea_dump_devname=/dev/pts/4 ; serial device descriptor for NMEA logging
PVT.flag_rtcm_server=false ; Enables or disables a TCP/IP server dispatching RTCM messages
PVT.flag_rtcm_tty_port=true ; Enables the RTCM log to a serial TTY port
PVT.rtcm_dump_devname=/dev/pts/1 ; serial device descriptor for RTCM logging

For hybrid GPS L1 / Galileo E1B receivers:

;######### PVT CONFIG ############
PVT.implementation=Hybrid_PVT
PVT.averaging_depth=10
PVT.flag_averaging=false
PVT.output_rate_ms=100;
PVT.display_rate_ms=500;
PVT.dump=false
PVT.dump_filename=./PVT

Notes on the output formats:

  • GeoJSON is a geospatial data interchange format based on JavaScript Object Notation (JSON) supported by numerous mapping and GIS software packages, including OpenLayers, Leaflet, MapServer, GeoServer, GeoDjango, GDAL, and CartoDB. It is also possible to use GeoJSON with PostGIS and Mapnik, both of which handle the format via the GDAL OGR conversion library. The Google Maps Javascript API v3 directly supports the integration of GeoJSON data layers, and GitHub also supports GeoJSON rendering.

  • KML (Keyhole Markup Language) is an XML grammar used to encode and transport representations of geographic data for display in an earth browser. KML is an open standard officially named the OpenGIS KML Encoding Standard (OGC KML), and it is maintained by the Open Geospatial Consortium, Inc. (OGC). KML files can be displayed in geobrowsers such as Google Earth, Marble, osgEarth, or used with the NASA World Wind SDK for Java.

  • NMEA 0183 is a combined electrical and data specification for communication between marine electronics such as echo sounder, sonars, anemometer, gyrocompass, autopilot, GPS receivers and many other types of instruments. It has been defined by, and is controlled by, the U.S. National Marine Electronics Association. The NMEA 0183 standard uses a simple ASCII, serial communications protocol that defines how data are transmitted in a sentence from one talker to multiple listeners at a time. Through the use of intermediate expanders, a talker can have a unidirectional conversation with a nearly unlimited number of listeners, and using multiplexers, multiple sensors can talk to a single computer port. At the application layer, the standard also defines the contents of each sentence (message) type, so that all listeners can parse messages accurately. Those messages can be sent through the serial port (that could be for instance a Bluetooth link) and be used/displayed by a number of software applications such as gpsd, JOSM, OpenCPN, and many others (and maybe running on other devices).

  • RINEX (Receiver Independent Exchange Format) is an interchange format for raw satellite navigation system data, covering observables and the information contained in the navigation message broadcast by GNSS satellites. This allows the user to post-process the received data to produce a more accurate result (usually with other data unknown to the original receiver, such as better models of the atmospheric conditions at time of measurement). RINEX files can be used by software packages such as GPSTk, RTKLIB and gLAB. GNSS-SDR by default generates RINEX version 3.02. If 2.11 is needed, it can be requested through a commandline flag when invoking the software receiver:

$ gnss-sdr --RINEX_version=2
  • RTCM SC-104 provides standards that define the data structure for differential GNSS correction information for a variety of differential correction applications. Developed by the Radio Technical Commission for Maritime Services (RTCM), they have become an industry standard for communication of correction information. GNSS-SDR implements RTCM version 3.2, defined in the document RTCM 10403.2, Differential GNSS (Global Navigation Satellite Systems) Services - Version 3 (February 1, 2013), which can be purchased online. By default, the generated RTCM binary messages are dumped into a text file in hexadecimal format. However, GNSS-SDR is equipped with a TCP/IP server, acting as an NTRIP source that can feed an NTRIP server. NTRIP (Networked Transport of RTCM via Internet Protocol) is an open standard protocol that can be freely download from BKG, and it is designed for disseminating differential correction data (e.g. in the RTCM-104 format) or other kinds of GNSS streaming data to stationary or mobile users over the Internet. The TCP/IP server can be enabled by setting PVT.flag_rtcm_server=true in the configuration file, and will be active during the execution of the software receiver. By default, the server will operate on port 2101 (which is the recommended port for RTCM services according to the Internet Assigned Numbers Authority, IANA), and will identify the Reference Station with ID=1234. This behaviour can be changed in the configuration file:
PVT.flag_rtcm_server=true
PVT.rtcm_tcp_port=2102
PVT.rtcm_station_id=1111

Important note:

In order to get well-formatted GeoJSON, KML and RINEX files, always terminate gnss-sdr execution by pressing key q and then key ENTER. Those files will be automatically deleted if no position fix have been obtained during the execution of the software receiver.

More documentation at the PVT Blocks page.

About the software license

GNSS-SDR is released under the General Public License (GPL) v3, thus securing practical usability, inspection, and continuous improvement by the research community, allowing the discussion based on tangible code and the analysis of results obtained with real signals. The GPL implies that:

  1. Copies may be distributed free of charge or for money, but the source code has to be shipped or provided free of charge (or at cost price) on demand. The receiver of the source code has the same rights meaning he can share copies free of charge or resell.
  2. The licensed material may be analyzed or modified.
  3. Modified material may be distributed under the same licensing terms but do not have to be distributed.

That means that modifications only have to be made available to the public if distribution happens. So it is perfectly fine to take the GNSS-SDR source code, modify it heavily and use it in a not distributed application / library. This is how companies like Google can run their own patched versions of Linux for example.

But what this also means is that non-GPL code cannot use GPL code. This means that you cannot modify / use GNSS-SDR, blend it with non-GPL code, and make money with the resulting software. You cannot distribute the resulting software under a non-disclosure agreement or contract. Distributors under the GPL also grant a license for any of their patents practiced by the software, to practice those patents in GPL software. You can sell a device that runs with GNSS-SDR, but if you distribute the code, it has to remain under GPL.

Publications and Credits

If you use GNSS-SDR to produce a research paper or Thesis, we would appreciate if you reference the following article to credit the GNSS-SDR project:

For LaTeX users, this is the BibTeX entry for your convenience:

@INPROCEEDINGS{GNSS-SDR11,
 AUTHOR = {C.~{Fern\'{a}ndez--Prades} and J.~Arribas and P.~Closas and C.~Avil\'{e}s and L.~Esteve},
 TITLE = {{GNSS-SDR}: An Open Source Tool For Researchers and Developers},
 BOOKTITLE = {Proc. of the ION GNSS 2011 Conference},
 YEAR = {2011},
 address = {Portland, Oregon},
 month = {Sept.} }

There is a list of papers related to GNSS-SDR in our publications page.

Ok, now what?

In order to start using GNSS-SDR, you may want to populate gnss-sdr/data folder (or anywhere else on your system) with raw data files. By "raw data" we mean the output of a Radio Frequency front-end's Analog-to-Digital converter. GNSS-SDR needs signal samples already in baseband or in passband, at a suitable intemediate frequency (on the order of MHz). Prepare your configuration file, and then you are ready for running gnss-sdr --config_file=your_configuration.conf, and seeing how the file is processed.

Another interesting option is working in real-time with a RF front-end. We provide drivers for UHD-compatible hardware such as the USRP family, for OsmoSDR and other front-ends (HackRF, bladeRF), for the GN3S v2 USB dongle and for some DVB-T USB dongles. Start with a low number of channels and then increase it in order to test how many channels your processor can handle in real-time.

You can find more information at the GNSS-SDR Documentation page or directly asking to the GNSS-SDR Developers mailing list.

You are also very welcome to contribute to the project, there are many ways to participate in GNSS-SDR. If you need some special feature not yet implemented, the Developer Team would love to be hired for developing it. Please do not hesitate to contact them.

Enjoy GNSS-SDR!

The Developer Team.