Dynamic sensor management algorithm based on improved efficacy function

A dynamic sensor management algorithm based on improved efficacy function is proposed to solve the multi-sensor faced to multi-target management problem. The tracking task precision requirements (PR), target priority (TP) and sensor used cost (SC) are considered to establish the efficacy function by weighted sums the normalized value of the three factors. The PR is described by the diversities of the desired covariance matrix and the predicted Covariance matrix which is obtained by the centralized sequential Kalman filtering algorithm. The TP model is established based on multi-attribute linear weighting and SC is estimated by practical experience. The simulation results proved that the proposed method can meet the requirements of PR and adjust sensor selection according to TP and SC. This makes sensor management scheme more reasonable and effective.