Qore Kalman module (kalman)

INTRODUCTION
------------
The Qore kalman module provides Kalman filter bindings on top of
Eigen (https://eigen.tuxfamily.org), the header-only C++ template
linear-algebra library. Kalman filters are the standard approach for
denoising / tracking / sensor-fusing noisy sequential observations —
their canonical applications are navigation (GPS/INS fusion, object
tracking), control systems, sensor processing in IoT and industrial
monitoring, and smoothing noisy time series in finance.

The module exposes three filter classes and a matrix primitive:

Classes provided:
    - Matrix:         columnar dense matrix (Eigen-backed); arithmetic,
                      transpose, inverse, cholesky, determinant.
    - LinearFilter:   standard Kalman filter (LKF) for linear systems.
    - ExtendedFilter: extended Kalman filter (EKF) for non-linear
                      dynamics / observations via Qore callbacks
                      returning Jacobians.

Pre-baked business-case helpers (1.1+):
    - ConstantVelocity2D / ConstantAcceleration2D / GpsSmoother —
      one-call construction of correctly-parameterised filters for
      common tracking problems.

Standalone functions:
    - kalman_version():   module version string.
    - get_kalman_info():  structured version info.

Thread safety: Matrix is immutable after construction (methods return
new matrices); filter objects hold mutable state and must not be
shared across threads without external locking.

DEPENDENCIES
------------
    - Eigen >= 3.3 (header-only; no runtime library)

BUILD
-----
    mkdir build && cd build
    cmake ..
    make
    sudo make install

Requires a Qore development installation (qore-config, qpp) and Eigen
development headers.

Matching distribution packages:
    - Ubuntu / Debian:  apt install libeigen3-dev
    - Alpine:           apk add eigen-dev
    - Fedora / RHEL:    dnf install eigen3-devel
    - macOS (Homebrew): brew install eigen