Improved joint probabilistic data association algorithm

Wang Ming-Hui1, Peng Ying-Ning1, You Zhi-Sheng2
1Electronics Engineering Department, Tsinghua University, Beijing, China
2Computer Science and Engineering Department, Sichuan University, Chengdu, China

Tóm tắt

The joint probabilistic data association (JPDA) filter has a very good tracking performance in dense targets and heavy clutter environments. However, the JPDA filter also has a huge computer load and tends to combine neighboring tracks. In this paper, an improved JPDA algorithm is presented. The main feature of our method is improving the performance of the JPDA algorithm by improving the performance of the tracking gate. The effectiveness of this method is assessed by mathematical analysis.

Từ khóa

#Target tracking #Q measurement #Gain measurement #Noise measurement #Time measurement #Size measurement #Filters #Mathematical analysis #Filtering #State estimation

Tài liệu tham khảo

bar-shalora, 1995, Multitarget-Multisensor Tracking Principles and Techniques kirubarajan, 1999, topography-based vs-imm estimator for large-scale ground target tracking, IEE Colloquium Target Tracking Algorithms and Applications, 11/1 wang, 2002, A performance optimized tracking gate algorithm, Acta Electronics Sinica, 28, 13 bar-shalom, 1988, Tracking and Data Association 10.1109/5.554210 10.1109/CDC.1995.478532 ahmeda, 1997, adaptive joint probabilistic data association algorithm for tracking multiple targets in cluttered environment, Radar Sonar and Navigation IEE Proceedings -, 144, 309, 10.1049/ip-rsn:19971585 bar-shalom, 1975, Tracking in A Cluttered Environment with Probability Data Association, 451 blackman, 1986, Multiple-Target Tracking with Radar Applications blom, 1992, Design of a multisensor lracking system for advanced air traffic control, Multitarget-Multisensor Tracking Applications and Advances