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This paper presents a processing framework to separate moving targets from the clutter, under multi-channel synthetic aperture radar (SAR) scenarios, and addresses the moving target imaging and velocity estimation problems for ground moving target indication (GMTI) applications. A practical implementation is introduced to break the SAR/GMTI problem into two processing stages, and the sparsity of the moving targets in the observed scene, is exploited throughout the stages. The two stage process extracts the moving targets from the monitored region via a sparsity-based iterative decomposition algorithm, and subsequently estimates the complete velocity vectors of moving targets by enforcing sparsity constraints. The model is sufficiently versatile to incorporate digital elevation map (DEM) information which further improves the moving target relocation accuracy. The effectiveness of the presented framework is demonstrated using Air Force Research Laboratory (AFRL) Gotcha GMTI challenge data.
|Journal||IEEE Transactions on Geoscience and Remote Sensing|
|Early online date||17 Sep 2018|
|Publication status||Published - 2018|
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- 1 Finished
Signal Processing in the Networked Battlespace
Mulgrew, B., Davies, M., Hopgood, J. & Thompson, J.
1/04/13 → 30/06/18