Blind Speed Compensation-Based Fast Iterative Adaptive Approach to Sidelobe Suppression for Fast Moving Targets

The iterative adaptive approach (IAA) has been shown to suppress sidelobes of strong targets effectively to the level of the noise, thereby unmasking weak targets nearby and yielding substantial sensitivity improvement over traditional pulse compression techniques. Unfortunately, heavy computational complexity is required to solve problems, including range cell migration, Doppler frequency migration, and high sidelobes encountered by multiple targets with high speed when adopting existing methods. As such, this article proposes a blind speed compensation (BSC)-based fast iterative adaptive approach. The proposed method first performs BSC-based coherent integration to concentrate most of the target energy within a small region in range-velocity domain effectively, which is helpful for the design of the adaptive filter with reduced dimensionality in the subsequent sidelobe suppression processing. Then, a partitioned IAA processing is applied on the data selected by a processing window centered around the target trajectory in BSC-based coherent integration result to correct residual migrations and suppress sidelobes. Both the BSC-based coherent integration preprocessing and the piecewise adaptive filtering can improve the computational efficiency with tolerable performance loss. Numerical simulations and experimental results illustrate that the proposed method enables efficient implementation schemes, resulting in low computational complexity while maintaining the performance benefit of sidelobe suppression and migration correction for fast moving targets.