Complexity reduction and clutter rank estimation for MIMO-phased STAP radar with subarrays at transmission

Abstract

Focused on reducing the complexity and the number of required training samples of space-time adaptive processing (STAP) technique, four typical classes of reduced-dimension (RD) algorithms are extended to the multiple-input multiple-output (MIMO) phased radar with transmitting subarrays. Then, a simple rule to estimate clutter rank in the reduced-dimension domain is derived. Some former rules in literature can be viewed as special cases of the proposed rule. Influences of orthogonality degradation of transmitting waveforms and other non-ideal factors are also analyzed. With this rule, more appropriate parameters of RD STAP processors can be determined, and thus better trade-off between system complexity and clutter suppression performance can be achieved. At last, simulated results with different conditions are utilized to assess the clutter suppression performance of the proposed algorithms and demonstrate the accuracy and applications of the proposed estimation rule.