Title :
Information fusion and tracking of maneuvering targets with artificial neural network
Author :
Zhongliang, Jing ; Hong, Xu ; Xueqin, Zhou
Author_Institution :
Dept. of Autom. Control, Northwestern Polytech. Univ., Xian, China
fDate :
27 Jun-2 Jul 1994
Abstract :
A novel algorithm for tracking manoeuvring targets is presented in this paper. This algorithm is implemented with a pair of parallel adaptive filters by the information fusion technique together with the current statistical model (CSM) and backpropagation (BP) neural network. In order to adapt to different cases of movement, BP network fuses all state information of both filters and adjusts the system variance for one of the filters according to the trained sample set. Computer simulation results show that this algorithm can successfully tracks manoeuvring targets over a wide range of conditions, and has a higher tracking precision
Keywords :
adaptive filters; backpropagation; filtering theory; neural nets; sensor fusion; target tracking; tracking; tracking filters; backpropagation; information fusion; maneuvering target tracking; neural network; parallel adaptive filters; state information; statistical model; system variance; Acceleration; Adaptive filters; Artificial neural networks; Computer simulation; Filtering algorithms; Information filtering; Information filters; Neural networks; Partial response channels; Target tracking;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374783
