PHD and CPHD Filtering With Unknown Detection Probability

A priori knowledge of target detection probability is of critical importance in the Gaussian mixture probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters. In addition, these two filters require that the process noise and measurement noise of the state propagated in the recursion be Gaussian. These limitations may restrict the two filters application in real problems. To accommodate unknown target detection probability and nonnegative non-Gaussian parameters, this paper propos