Title :
Multisensor multiple-attribute data association
Author :
Jing, Jiang ; Jing, Guo ; Fei, Luo Peng ; Sheng, Liu Fu ; Kong, Sun Zhong
Author_Institution :
Dept. of Electron. Technol., Nat. Univ. of Defence Technol., Changsha, China
Abstract :
A multisensor system can provide a variety of target information (including dynamic parameters and attribute parameters). Target dynamic parameters are regarded as a kind of target kinematic attribute. A probability assignment method is explained in two cases both of process noise and measurement noise being Gaussis statistics and of being non-Gaussis statistics. A multisensor multiple-attribute data association method is presented based on Dempster and Shafer (D-S) evidence theory, and this approach is illustrated by simulations involving multisensor multiple targets in a dense clutter environment. Comparison with the NN (nearest-neighbour) method which only uses target dynamic parameters shows that the approach has an improved tracking accuracy and resolved correlation ambiguity
Keywords :
Gaussian processes; correlation methods; parameter estimation; probability; radar clutter; radar signal processing; radar tracking; sensor fusion; statistical analysis; Dempster-Shafer evidence theory; Gaussis statistics; air defence radar systems; attribute parameters; dense clutter environment; dynamic parameters; measurement noise; multisensor multiple attribute data association; multisensor system; nearest-neighbour method; nonGaussis statistics; probability assignment method; process noise; resolved correlation ambiguity; simulations; target information; target kinematic attribute; tracking accuracy; Acoustic sensors; Clutter; Gaussian noise; Infrared sensors; Multisensor systems; Radar cross section; Radar tracking; Sensor systems; Target tracking; Working environment noise;
Conference_Titel :
Radar, 1996. Proceedings., CIE International Conference of
Conference_Location :
Beijing
Print_ISBN :
0-7803-2914-7
DOI :
10.1109/ICR.1996.574474
