Mitigation of Biologically Induced Active Sonar Reverberation in Littoral Regions

Applied Research in Acoustics LLC has formulated and developed and evaluated the feasibility 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 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. Based on the positive results achieved in Phase I, ARiA proposes a Phase II effort to further develop and evaluate the algorithms and perform development and integration efforts that will enable transition to the AN/SQQ89A(V)15 surface-ship tactical system.