Title :
Improved joint probabilistic data association algorithm
Author :
Ming-Hui, Wang ; Ying-ning, Peng ; Zhi-Sheng, You
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
clutter; filtering theory; mathematical analysis; sensor fusion; target tracking; dense targets; heavy clutter environment; improved joint probabilistic data association algorithm; joint probabilistic data association filter; mathematical analysis; tracking gate; tracking performance; Filtering; Filters; Gain measurement; Mathematical analysis; Noise measurement; Q measurement; Size measurement; State estimation; Target tracking; Time measurement;
Conference_Titel :
Information Fusion, 2002. Proceedings of the Fifth International Conference on
Conference_Location :
Annapolis, MD, USA
Print_ISBN :
0-9721844-1-4
DOI :
10.1109/ICIF.2002.1021009
