A probability hypothesis density filtering algorithm based on information association weighting is proposed to address the two issues of decreased accuracy in multi-target state estimation and overestimation of the number of multi-targets， which are caused by asynchronicity and high-density clutter aliasing in passive and active radar detection information across multiple platforms. Firstly， a multi-target tracking model is constructed， and the mechanism of why existing algorithms are susceptible to clutter is analyzed. Secondly， a multi-target tracking algorithm based on information association weighting is derived. The tolerance time parameter is set according to the target speed and tolerable error， and the detection information with a short asynchronous time is approximated as synchronous information. The association algorithm is used to select passive and active radar information from the same target， and the minimum variance weighted fusion is used to improve detection accuracy. The randomly distributed clutter is filtered out， due to its association difficulties caused by large differences in angle values. Finally， simulation analysis shows that the proposed algorithm improves the accuracy of multi-target state estimation and reduces the overestimation of the number of multi-targets compared to existing algorithms.

To solve the optimal configuration design problem in passive and active passive multi-platform collaborative tracking scenarios， a multi-platform collaborative tracking optimal configuration design method based on effectiveness evaluation system is proposed. The mathematical model of passive and active passive multi-platform cooperative tracking is derived， and the effectiveness that can evaluate the tracking results is selected as the tracking effectiveness. A quantitative function is designed to unify the tracking effectiveness dimension； the analytic hierarchy process is used to construct a tracking effectiveness evaluation system， and a formula for calculating the effectiveness evaluation value is derived. In order to obtain the optimal configuration parameters， establish a maximum effectiveness evaluation value， consider the optimal design problem constrained by the range of configuration parameters and communication rate； then， the differential evolution algorithm is used to solve the optimal design problem. The final simulation results show that the proposed method can obtain the optimal configuration parameters and complete the configuration design with the optimal tracking effectiveness evaluation value.