Mitigation of Biologically Induced Active Sonar Reverberation in Littoral Regions

Applied Research in Acoustics LLC will formulate and develop new concepts and algorithms for data-driven clutter-adaptive waveform-synthesis and CFAR normalization processing based on physical models of resonant backscattering from heterogeneous aggregations of swim-bladder-bearing fish that will significantly improve active sonar detection capability in littoral waters by reducing the number of false contacts and decreasing the amount of display clutter. The new signal processing concepts and algorithms developed and evaluated in this work will comprise (1) clutter-adaptive waveform and matched-filter synthesis using a data-driven approach to mitigate reverberation and clutter due to resonant scattering from fish, (2) clutter-adaptive CFAR normalization of the within-beam time series using model-based and data-driven assessment of range-dependent amplitude statistics, and (3) clutter-adaptive cross-beam and image-based normalization using model-based and data-driven assessment of spatial statistics of clutter from fish. The performance and feasibility of these new concepts and algorithms will be evaluated individually and as an integrated processing system with simulated midfrequency active sonar data representative of the AN/SQS-53C operating in a shallow-water environment with various sources of biologically induced clutter, as generated by a validated sonar-simulation model and a validated analytical model of scattering from heterogeneous aggregations of swim-bladder-bearing fish.