MIPS is a tool for simulating the performance of incoherent scatter radar systems and networks of such radars. MIPS is a physics based radar performance model that incorporates first and second order effects and measurement statistics. The model is parameterized and allows straightforward optimization and design tradeoffs to be evaluated for IS radar performance metrics (e.g. SNR, measurement speed, estimation errors, etc).
For incoherent scatter radar (IS radar) applications studying the near-Earth space environment, the instrument design parameter space for a modern Geospace Radar is very large. Particular areas of design freedom include transmitted waveforms (e.g. required bandwidth, center frequency, duty cycle), array configuration (e.g. element number and configuration), spatial diversity (monostatic vs. locally bistatic), receiver sensitivity tradeoffs, and power-aperture product choices (e.g. high power with few elements versus low power with many elements).
| Official source code repo: | https://github.com/MITHaystack/MIPS |
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| Issue tracker: | https://github.com/MITHaystack/MIPS/issues |
If you use MIPS in a scientific publication, we would appreciate a citation such as the following (BibTeX):
P. J. Erickson, J. Vierinen, F. D. Lind and R. Volz, "The MIT Incoherent Scatter Performance Simulator (MIPS)," 2017 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), 2017, pp. 1-2, doi: 10.1109/USNC-URSI-NRSM.2017.7878319.
The main package components are in the source directory and are divided into MIPS related libraries and examples of using the simulator.
python
- madrigalWeb
- numpy
- scipy
- matplotlib
- xarray
- yamale
- h5py
- iri2016
- ISRSpectrum>=3.2.2
- h5netcdf
- netcdf4
- astropy
- cartopy
Make sure the above libraries have been installed.
Create the Python distribution file:
python setup.py bdist_egg
Then install using pip:
pip install -e .
A small set of Python examples can be found in the examples directory in the source tree.
MIPS usage can be somewhat complex due to the wide range of radar configurations, ionospheric conditions, and subtleties related to coding and radar scattering geometry.
cd examples
- python mips_performance_sim.py
- python mips_zenith_comparison.py
- python mips_misa_mapping.py
- python mips_esicat3d_mapping.py
It is recommended that you discuss applications of MIPS with the development team prior to use in any publications.
This work was supported by the National Science Foundation under the AGS Geospace Facilities program. We are grateful for the support that made this development possible.