Title :
Multi-sensor management: Optimal allocation of tracking resources for Pd < 1 based on the interacting multiple model modified kalman filter
Author :
Jun, Tong ; Shan Gan-lin
Author_Institution :
Dept. of Opt. & Electron. Eng., Coll. of Mech. Eng., Shijiazhuang, China
Abstract :
This paper presents a novel sensor selection algorithm for optimal allocation of target tracking resources, based on the interacting multiple model modified kalman filter. The algorithm can be easily calculated and it is possible to include sensors with a probability of detection Pd <;1. The sensor selection measure function is the minimum trace of covariance matrix. The performance of the sensor selection algorithm is studied for single sensor and sensor collocation. And simulation shows the method is effective and feasible.
Keywords :
Kalman filters; covariance matrices; probability; resource allocation; sensor fusion; target tracking; covariance matrix; detection probability; interacting multiple model modified Kalman filter; multisensor management; optimal target tracking resource allocation; sensor collocation; sensor selection algorithm; Covariance matrix; Kalman filters; Mathematical model; Optimization; Radar tracking; Target tracking; IMMMKF; measure function; multi-sensor management; sensor selection; trace;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5777375