Multi-sensor Multi-Target Detection Based on Joint Probability Density

摘要

Joint probability density algorithm (JPDA) is extended to multi-sensor multi-target detection based on 'Clean' method. Key content and characteristic of JPDA in false intersection points eliminating are introduced. An iterative method for multi-sensor multi-target detection is put forward. Based on target that has been detected by peak searching, an inverse probability density function is proposed which is able to eliminate both the detected target and false intersection points. A new joint probability density matrix is constructed and all the targets can be detected through iterative process. The feasibility and validity are verified through simulation.