Title :
Improvement of multisensor data fusion on track loss in clutter
Author :
Ningzhou, Cui ; Weixin, Xie ; Yu Xiongnan ; Yuanliang, Ma
Author_Institution :
Dept. of Electron. Eng., Xidian Univ., Xi´´an, China
Abstract :
Improvement of multisensor data fusion on track loss in clutter is studied analytically in this paper. Calculating the transition probability density function of the fusion prediction error, the authors have analyzed the dependence of the fusion track loss statistics, such as mean time to lose track and cumulative probability of having lost track, on the clutter spatial density for nearest-neighbor association. The results show that multisensor data fusion can improve the tracking performance in clutter with low track loss probability
Keywords :
probability; radar clutter; radar tracking; sensor fusion; target tracking; clutter spatial density; fusion prediction error; fusion track loss statistics; multisensor data fusion; nearest-neighbor association; radar clutter; track loss probability; tracking performance; transition probability density function; Covariance matrix; Filters; Gaussian noise; Neural networks; Probability; Sensor fusion; State estimation; Target tracking; Technological innovation; White noise;
Conference_Titel :
Radar, 1996. Proceedings., CIE International Conference of
Conference_Location :
Beijing
Print_ISBN :
0-7803-2914-7
DOI :
10.1109/ICR.1996.574592
