Post pulse compression and partially adaptive multi‐waveform STAP

Abstract

The recently developed multi-waveform space-time adaptive processing (µ-STAP) formulation incorporates additional training data into the sample covariance matrix estimate by applying multiple different secondary pulse compression filters to the raw received data, where these filters have a relatively low cross-correlation with the transmitted waveform. The inclusion of this additional training data has been shown to improve robustness to non-homogeneous clutter due to a ‘range smearing’ homogenising effect of the secondary filters. Here, the authors introduce post µ-STAP (Pµ-STAP), a new form of µ-STAP that similarly generates additional training data, albeit after pulse compression has already occurred. In addition, we combine Pµ-STAP with well-known partially adaptive STAP techniques to assess whether the enhanced performance is retained for reduced-dimension operation. Specifically, element-space post-Doppler, beam-space pre-Doppler, and beam-space post-Doppler implementations of Pµ-STAP are evaluated via signal-to-interference-plus-noise ratio analysis and minimum detectable Doppler for different simulated clutter environments.