Presenting a New Technique for Multi-Target Tracking in Inverse Synthetic Aperture Radar based on PHD Filter in the Presence of Clutters

Abstract

Using Probability Hypothesis Density (PHD) filtering, a novel approach is proposed in this paper for simultaneous tracking of multiple moving targets in received data by Inverse Synthetic Aperture Radar (ISAR) system. Since PHD filtering approach is implemented successively in prediction and update steps, its performance quality will obviously be higher in “Spotlight” imaging mode than in “Stripmap”. Thus, its application to Spotlight mode is generally more logical. The idea to integrate tracking capability into ISAR system processor is to sort radar received data to correct Range Cell Migration (RCM) prior to tracking operations. Clearly, Range Cell Migration Compensation (RCMC) approach is different from this approach in image formation process, in terms of their implementation phase. However, they are implemented in a similar way. As simulation results reveal, applying Range Cell Migration Compensation to the raw data received by ISAR before tracking operation, results in high quality tracking of moving targets.

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 desirable simplification of the above relations, which are expressed in a closed form, is depicted in Vo et al () and Vo and Ma (). Moreover, by applying the RCMC approach to the SAR observations, the GM‐PHD and SMC‐PHD filtering relations can be updated (Daryasafar et al, ; Dehghani & Daryasafar, ).…”

“…In this part, the tracking results were examined for different clutter values, based on the promoted GM-PHD filtering (Daryasafar et al, 2017) and the promoted SMC-PHD filtering (Dehghani & Daryasafar, 2018).…”