Aiming at problem that performance degradation problem of Gaussian mixture probability hypothesis density（ GM-PHD） filter caused by non-prior detection probability and invalid measurement

a multi-target PHD filter based on the time-varying Kalman filtering（ TV-KF） algorithm is proposed. Elliptical gate is used to preassociate target sets and measurement sets

unknown detection probability is converted to and target loss and receiving event. Targets are divided into matched-survival targets

matched-birth targets and non-matched targets.For matched targets

only the measurements in threshold are used to update target state; for non-matched targets

their weights are decayed. The simulation results show that the proposed algorithm is feasible

effective and outperforms the traditional GM-PHD algorithm.