TY - GEN
T1 - Multi-sensor Bearings-only Target Tracking Using Two-stage Multiple Hypothesis Tracking
AU - Wei, Zheng
AU - Duan, Zhansheng
AU - Han, Yina
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The problem of multi-sensor bearings-only target tracking is addressed in this work. A practical challenge in this problem stems from the data association in dense clutter. In order to avoid the increase of computational complexity with the increase of the number of sensors and clutter density, a two-stage multiple hypothesis tracking (MHT) algorithm is proposed. First, the first stage MHT is performed at each local sensor, and the measurements with effective data association are sent to the fusion center. Second, the measurements from different sensors are combined and augmented to form new measurement vectors, which are then converted to Cartesian coordinates by iterated least squares (ILS) estimator. Therefore, in the second stage MHT, the Kalman filter can be used to update the target track. The performance of the two-stage MHT algorithm is illustrated with an example.
AB - The problem of multi-sensor bearings-only target tracking is addressed in this work. A practical challenge in this problem stems from the data association in dense clutter. In order to avoid the increase of computational complexity with the increase of the number of sensors and clutter density, a two-stage multiple hypothesis tracking (MHT) algorithm is proposed. First, the first stage MHT is performed at each local sensor, and the measurements with effective data association are sent to the fusion center. Second, the measurements from different sensors are combined and augmented to form new measurement vectors, which are then converted to Cartesian coordinates by iterated least squares (ILS) estimator. Therefore, in the second stage MHT, the Kalman filter can be used to update the target track. The performance of the two-stage MHT algorithm is illustrated with an example.
KW - Iterated least squares
KW - Multi-sensor bearings-only tracking
KW - Multiple hypothesis tracking
UR - https://www.scopus.com/pages/publications/85123989856
U2 - 10.1109/ICCAIS52680.2021.9624486
DO - 10.1109/ICCAIS52680.2021.9624486
M3 - 会议稿件
AN - SCOPUS:85123989856
T3 - 10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021 - Proceedings
SP - 711
EP - 716
BT - 10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Control, Automation and Information Sciences, ICCAIS 2021
Y2 - 14 October 2021 through 17 October 2021
ER -