Improving multitarget tracking in synthetic aperture radar within a high-density clutter, using a technique based on the promoted PHD filtering and MTI filter

A method is presented in this paper for simultaneous multitarget tracking in the presence of high-density clutter through the received data by synthetic aperture radar (SAR) by the use of the promoted Gaussian mixture probability hypothesis density filtering. Simultaneous tracking of several moving targets in an environment with high density of clutters is a special feature of probability hypothesis density (PHD) filtering that has turned it into a powerful system for tracking moving targets in SAR. Moving targets are desirably tracked by applying range cell migration compensation on the raw data received by SAR. As simulation results revealed, applying moving target indicator (MTI) filter before tracking process could improve performance of the promoted PHD filtering in multitarget tracking in SAR radar. In other words, application of MTI filter to decrease the clutter would significantly reduce the computational loads of the processor in tracking moving targets through the reduction of observations that enter the processor. The main parameters for assessing the performance of the proposed algorithm in this paper, the extracted state of moving targets over time in the presence of noise for different values of clutter's density, are considered in received observations. By increasing clutter density, the tracking process will be carried out with poorer performance using the promoted Gaussian mixture probability hypothesis density and Sequential Monte Carlo-PHD filterings.