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

One of the challenges of airborne radar construction is to provide reliable detection of low radar cross section targets of different velocities (e.g. unmanned aerial vehicle) in presence of clutter. In existing pulse Doppler radar signal parameters variation is used: high repetition frequency for head-on course targets, middle repetition frequency for pursuit course targets. Although radar range of low radar cross section targets on pursuit course appears to be insufficient. The aim of the study is to develop space-time adaptive processing (STAP) algorithm for phased array multi-input-multi-output airborne pulse Doppler radar for low Doppler targets detection in clutter environment and to analyze its efficiency. The paper provides comparative efficiency analysis of different signal processing algorithms for targets detection in clutter environment. According to computer modeling results optimal STAP algorithms could lower energy losses (20-25 dB) and increase radar range for low radar cross section targets detection on pursuit courses compared to factored approaches of beamforming followed by Doppler filtering. Meanwhile in practice it's difficult to provide sample support required for optimal STAP algorithm (about 2-103-2?104). It's shown that linear transformation (beamspace post-Doppler processing) could reduce dimensionality of the unknown interference parameters up to 30-50 at energy losses about 3-5 dB with required sample support about 60-100. The article presents an algorithm for further reduction of dimensionality based on apriori knowledge of clutter structure. The algorithm suggests reduction of dimensionality of the unknown interference parameters up to 3-5 at energy losses about 5 dB with required sample support about 6-10.