R.S. Tikhonov - Research Scientist, LLC «Radio Electronic Technologies». E-mail: tam@inbox.ru

One of the crucial issues for airborne radar developers is to increase maximum detection range of airborne targets. It is especially difficult for low flying receding targets due to terrain clutter influence. In existing radars radar signals with medium pulse-repetition frequency for receding target detection are used. Although maximum detection range provided for low radar cross section receding targets is often insufficient. Nowadays advanced radars are equipped with multi-input-multi-output phased arrays antennas, due to this the adoption of space-time adaptive processing (STAP) for target detection in terrain clutter environment is possible. However practical implementation of STAP algorithms faces some difficulties caused by clutter covariance matrix estimation at limited sample support and computational complexity of its inversion. The paper considers STAP algorithm with low sample support requirements and computational complexity for low flying targets detection in terrain clutter environment. The algorithm is based on apriori knowledge of clutter characteristics for different bins. The algorithm could significantly reduce (for 15-20 dB) clutter energy losses for low flying receding targets compared to conventional signal processing with sequential beamforming and Doppler processing (for the same radar signal parameters).

 

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