Adaptive pulse compression for clutter mitigation in midfrequency active sonar

Midfrequency active sonar can achieve a combination of fine range resolution and good signal-to-noise ratio (SNR) by transmitting low-crest-factor frequency-modulated (FM) waveforms that are pulse compressed by match filtering. While this linear filter optimizes SNR for signals in additive Gaussian noise, it has large-amplitude range sidelobes that can allow strong sources of clutter, such as fish schools, to mask weaker nearby targets. To address range sidelobes we consider the reiterative minimum mean-square error (RMMSE) adaptive-pulse-compression algorithm [Blunt and Gerlach, Proc. IEEE Intl. Radar Conf., Sept. 2003]. RMMSE performance is known to degrade for small Doppler shifts in the received waveform (e.g., due to clutter internal motion), which, depending on the form of the FM sweep, can be partially mitigated by covariance-matrix tapers [Cuprak, M.S. Thesis, George Mason University, 2013]. We note that RMMSE is analogous to the minimum-variance distortionless-response (MVDR) beamformer: for each range cell it steers nulls the location of strong returns at nearby range samples. Motivated by this similarity and expectation of target sparsity in range, we extend the compressive beamforming approach developed in prior work to learning a compressive-sensing match filter. Preliminary results from this work are discussed. [Work supported by a NAVSEA Phase I SBIR award.]