Multi-target tracking random finite set model based on signal parameter correlation

Abstract

The target is generally equipped with a corresponding radiation source, and the signal parameter of the radiation source can be used as an important auxiliary parameter to improve the tracking performance of the electronic reconnaissance system to the target. For the practical application scenario of multi-tracking, we proposes an improved Gaussian mixture probability hypothesis density filter (GMPHD) filtering algorithm based on the correlation of radiation source signal parameters. By using the signal parameters to expand the dimension of the target’s motion state vector, the description of the target state is improved. Based on the statistical theory of random finite sets, the multi-target state is described as a random finite set, and GMPHD is used for tracking. Simulation results show that the use of signal parameters can enhance the precision of data correlation, thereby improving the performance of the trace.