This GitHub repository contains the scripts for the IEEE ICASSP 2024 paper submission: "Multi-Sensor Multi-Scan Radar Sensing of Multiple Extended Targets"; Martin V. Vejling, Christophe A. N. Biscio, and Petar Popovski, 2023.
Author: Martin Voigt Vejling
E-Mails: mvv@math.aau.dk, mvv@es.aau.dk, martin.vejling@gmail.com
In this work a doubly inhomogeneous generalized shot noise Cox process model is proposed to model the measurement process in multi-sensor multi-scan multiple extended object radar sensing scenarios. An estimation procedure based on jump Markov chain Monte Carlo is provided to do target state estimation. For comparison, a spatial proximity baseline is provided in the DBSCAN algorithm with hyperparameters optimized by the posterior of the aforementioned model. Moreover, a theoretically optimal oracle method is also given for comparison.
This project is created with Python 3.11.4
Dependencies:
matplotlib 3.7.2
numpy 1.25.2
scipy 1.11.1
scikit-learn 1.2.2
toml 0.10.2
tqdm 4.66.1
line_profiler 4.0.3
tikzplotlib 0.10.1
multiprocess 0.70.15
To use this GitHub repository follow these steps:
- Install Python with the dependencies stated in the Dependencies section.
- Choose numerical experiment settings in sensing_filter.toml.
- Run sensing_filter_main.py.