Estimation of Ground Moving Target Parameters in Arc-SAR Using Meta-Heuristic Optimization Algorithms

A practical method is proposed for ground-based Arc-SAR (Arc-scanning Synthetic Aperture Radar) for detection of moving targets and extraction of their motion parameters. Since the Arc-SAR scans the environment rotationally and repeatedly, a clutter map can be generated from previous scans and subtracted from new scan to cancel the effect of clutter (fixed targets) and reveal moving targets. To obtain the moving target parameters, we used the clutter-cancelled received signal and defined an optimization problem to maximize the similarity of the received signal with the simulated signal of an assumed moving target. The optimization problem is solved by some classic and meta-heuristic optimization algorithms. Simulation results show that even under severe noise and clutter conditions, the position, velocity, and acceleration of the moving target can be accurately estimated, but the results of the meta-heuristic algorithm are more accurate at the cost of more execution time.