A Novel Approach to Moving Target Screening for UHF-Band SAR GMTI

A Novel Approach to Moving Target Screening for UHF-Band SAR GMTI


Due to a long coherent processing interval, moving targets are severely smeared in the UHF-band synthetic aperture radar (SAR) imagery. This further results in a low signal to- clutter-and-noise ratio, which might lead to an unacceptable false-alarm rate in multichannel ground moving target indication. A method of moving target screening is presented in this letter, which serves to determine whether the target detected by a constant false-alarm rate detector is a real moving target. An inverse omega-K algorithm is implemented, which can recover the Doppler phase history of any isolated target within a clutter suppressed omega-K SAR image. The recovered data are again processed into a subimage by a simple range-Doppler algorithm. Then, the subimage is refocused by azimuth autofocus processing. The sharpness of the subimage will not change after refocusing if it only contains stationary targets; otherwise, the sharpness will significantly improve. We can eliminate a false moving target by detecting this change. The proposed method is demonstrated on simulated and real multichannel UHF-band SAR data.

Existing System:

In multichannel SAR GMTI, the responses of moving targets are reserved after clutter suppression. Meanwhile, the responses of some strong stationary scatters are also reserved because of the mismatch between receiving channels. All these responses can be detected by a CFAR detector. It is always hard to tell which responses belong to moving targets. Therefore, seeking a way to screen out the moving targets becomes a practical and significant research topic.


Refocusing a subimage is feasible to distinguish between moving and stationary targets. In, this method is designed for single-channel SAR moving target detection. However, its performance is heavily affected by stationary responses because the clutter and the moving target experience different Doppler phase histories.

Proposed System:

Finally, clutter suppression and CFAR detection are implemented to detect suspected moving targets. In the second stage, moving targets are screened out from the suspected targets detected by the CFAR technique. The blurred moving targets in the clutter suppressed SAR imagery are refocused to distinguish them from the stationary targets. To this end, the moving target’s Doppler phase history is recovered to provide input data for subsequent moving target imaging processing.