Kotelnikov Institute of Radio Engineering and Electronics of RAS Русский Sign in Submit a paper
Journal of Radio Electronics Online scientific journal · eISSN 1684-1719
2023, № 7 · RADAR INFORMATION METHODS AND ELEMENTS

Nonlinear filtering for the state of extended targets

B.T. Le1

1 Moscow Institute of Physics and Technology (National Research University), Dolgoprudnyi, Russia
Full text (PDF) DOI: 10.30898/1684-1719.2023.7.8 UDC 621.396.965.8 EDN ZBIAWM

Abstract

This paper introduces a novel algorithm for multi-extended object tracking, which is based on probabilistic-statistical modelling, machine learning, and optimization theory. The proposed approach encompasses methods for modelling the state of extended objects, data association, and predicting and updating the state of extended objects at each time step. The performance of the algorithm was assessed and compared with other existing algorithms using simulation modelling in MATLAB. This simulation emulates scenarios in which extended objects are tracked while moving under various noise levels. Simulation results demonstrate that the algorithm can effectively detect and track the trajectories of multiple extended objects under different noise levels, utilizing both linear and non-linear measurements from an array of sensors. Furthermore, the algorithm estimates not only the number and kinematic states of the targets but also provides an approximate evaluation of their size.

  • extended object tracking
  • nonlinear filtering
  • extended target
Аннотация (на русском)

Нелинейная фильтрация сигналов распределенной движущейся цели при траекторной обработке

На основе методов статистического вероятностного моделирования разработан алгоритм фильтрации состояния протяженной цели. Алгоритм позволяет предсказывать и обновлять кинематические и протяженные состояния цели, используя как линейные, так и нелинейные модели и измерения, включая радиальную скорость от датчиков высокого разрешения, таких как автомобильные радары или лидары. Путем проведения экспериментов с использованием метода имитационного моделирования в программной среде MATLAB оценена эффективность алгоритма.

For citation

Le B.T. Nonlinear filtering for the state of extended targets // Journal of Radio Electronics. – 2023. – No. 7. https://doi.org/10.30898/1684-1719.2023.7.8

References

  1. Кичерова А. Д., Медведев Е. Р. Программная реализация вторичной обработки сигналов в автомобильном радаре //Навигация и управление движением. - 2021. - С. 277-279.
  2. Buhren M., Yang B. Simulation of automotive radar target lists using a novel approach of object representation //2006 IEEE Intelligent Vehicles Symposium. - IEEE, 2006. - С. 314-319. https://doi.org/10.1109/IVS.2006.1689647
  3. Gunnarsson J. et al. Tracking vehicles using radar detections //2007 IEEE Intelligent Vehicles Symposium. - IEEE, 2007. - С. 296-302. https://doi.org/10.1109/IVS.2007.4290130
  4. Hammarstrand L. et al. Extended object tracking using a radar resolution model //IEEE Transactions on Aerospace and Electronic Systems. - 2012. - Т. 48. - №. 3. - С. 2371-2386. https://doi.org/10.1109/TAES.2012.6237597
  5. Gilholm K. et al. Poisson models for extended target and group tracking //Signal and Data Processing of Small Targets 2005. - SPIE, 2005. - Т. 5913. - С. 230-241. https://doi.org/10.1117/12.618730
  6. Gilholm K., Salmond D. Spatial distribution model for tracking extended objects //IEE Proceedings-Radar, Sonar and Navigation. - 2005. - Т. 152. - №. 5. - С. 364-371. https://doi.org/10.1049/ip-rsn:20045114
  7. Ristic B., Sherrah J. Bernoulli filter for detection and tracking of an extended object in clutter //2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. - IEEE, 2013. - С. 306-311. https://doi.org/10.1109/ISSNIP.2013.6529807
  8. Granström K., Lundquist C. On the use of multiple measurement models for extended target tracking //Proceedings of the 16th International Conference on Information Fusion. - IEEE, 2013. - С. 1534-1541. https://ieeexplore.ieee.org/abstract/document/6641184
  9. Granström K. et al. PHD extended target tracking using an incoherent X-band radar: Preliminary real-world experimental results //17th International Conference on Information Fusion (FUSION). - IEEE, 2014. - С. 1-8. https://ieeexplore.ieee.org/document/6916272
  10. Granström K. et al. Gamma Gaussian inverse Wishart probability hypothesis density for extended target tracking using X-band marine radar data //IEEE Transactions on Geoscience and Remote Sensing. - 2015. - Т. 53. - №. 12. - С. 6617-6631. https://doi.org/10.1109/TGRS.2015.2444794
  11. Knill C., Scheel A., Dietmayer K. A direct scattering model for tracking vehicles with high-resolution radars //2016 IEEE Intelligent Vehicles Symposium (IV). - IEEE, 2016. - С. 298-303. https://doi.org/10.1109/IVS.2016.7535401
  12. Lian F. et al. Unified cardinalized probability hypothesis density filters for extended targets and unresolved targets //Signal Processing. - 2012. - Т. 92. - №. 7. - С. 1729-1744. https://doi.org/10.1016/j.sigpro.2012.01.009
  13. Petrovskaya A., Thrun S. Model based vehicle detection and tracking for autonomous urban driving //Autonomous Robots. - 2009. - Т. 26. - №. 2-3. - С. 123-139. https://doi.org/10.1007/s10514-009-9115-1
  14. Scheel A., Reuter S., Dietmayer K. Using separable likelihoods for laser-based vehicle tracking with a labeled multi-Bernoulli filter //2016 19th International Conference on Information Fusion (FUSION). - IEEE, 2016. - С. 1200-1207. https://ieeexplore.ieee.org/document/7528021
  15. Koch J. W. Bayesian approach to extended object and cluster tracking using random matrices //IEEE Transactions on Aerospace and Electronic Systems. - 2008. - Т. 44. - №. 3. - С. 1042-1059. https://doi.org/10.1109/TAES.2008.4655362
  16. Feldmann M., Fränken D., Koch W. Tracking of extended objects and group targets using random matrices //IEEE Transactions on Signal Processing. - 2010. - Т. 59. - №. 4. - С. 1409-1420. https://doi.org/10.1109/TSP.2010.2101064
  17. Orguner U. A variational measurement update for extended target tracking with random matrices //IEEE Transactions on Signal Processing. - 2012. - Т. 60. - №. 7. - С. 3827-3834. https://doi.org/10.1109/TSP.2012.2192927
  18. Ardeshiri T., Orguner U., Gustafsson F. Bayesian inference via approximation of log-likelihood for priors in exponential family //arXiv preprint arXiv:1510.01225. - 2015. https://doi.org/10.48550/arXiv.1510.01225
  19. Lan J., Li X. R. Tracking of extended object or target group using random matrix-Part I: New model and approach //2012 15th International Conference on Information Fusion. - IEEE, 2012. - С. 2177-2184. https://ieeexplore.ieee.org/document/6290568
  20. Vivone G., Braca P., Errasti-Alcala B. Extended target tracking applied to X-band marine radar data //OCEANS 2015-Genova. - IEEE, 2015. - С. 1-6. https://doi.org/10.1109/OCEANS-Genova.2015.7271630
  21. Vivone G. et al. Converted measurements Bayesian extended target tracking applied to X-band marine radar data. - 2019.
  22. Vivone G. et al. Multistatic Bayesian extended target tracking //IEEE Transactions on Aerospace and Electronic Systems. - 2016. - Т. 52. - №. 6. - С. 2626-2643. https://doi.org/10.1109/TAES.2016.150724
  23. Schumann O. et al. RadarScenes: A real-world radar point cloud data set for automotive applications //2021 IEEE 24th International Conference on Information Fusion (FUSION). - IEEE, 2021. - С. 1-8. https://doi.org/10.23919/FUSION49465.2021.9627037
  24. Gelman A. et al. Bayesian data analysis. - CRC press, 2013. https://doi.org/10.1201/b16018
  25. Granström K., Orguner U. Estimation and maintenance of measurement rates for multiple extended target tracking //2012 15th International Conference on Information Fusion. - IEEE, 2012. - С. 2170-2176. https://ieeexplore.ieee.org/document/6290567
  26. Li X. R., Zhao Z., Jilkov V. P. Practical measures and test for credibility of an estimator //Proc. Workshop on Estimation, Tracking, and Fusion-A Tribute to Yaakov Bar-Shalom. - Citeseer, 2001. - С. 481-495. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1c1f6c864789630d8cd37d5342f67ad8d480f077
  27. Su J. et al. Underwater 3d doppler-angle target tracking with signal time delay //Sensors. - 2020. - Т. 20. - №. 14. - С. 3869. https://doi.org/10.3390/s20143869
  28. Bar-Shalom Y., Li X. R., Kirubarajan T. Estimation with applications to tracking and navigation: theory algorithms and software. - John Wiley & Sons, 2001.https://doi.org/10.1002/0471221279.ch11