Algorithms for Rapid and Accurate Depth Localization of Targets for Mine Avoidance
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AbstractThe US Navy's new DD(X) destroyer currently under design features amongst its extensive sensor suite an innovative dual (high frequency and mid-frequency) frequency, active bow sonar. One of the primary missions of the high frequency (HF) component of the bow-sonar will be in-stride mine avoidance. Advanced signal processing algorithms, developed for predecessor sonars aboard modern US submarines, allow high-resolution localization (range, depth and relative azimuth) of mine-like objects. However, the performance of these algorithms is degraded under multipath conditions typical of shallow water (<200m) environments. Here we propose to investigate, develop, demonstrate and implement modifications to the existing signal processing sequence to improve the sonar's mine-hunting capabilities in refractive, multipath environments. These modifications will be implemented in a robust, post-monopulse correlated-field-processing algorithm. The proposed algorithm will endeavor to simultaneously estimate both target location and relevant environmental parameters by comparing the beam-time structure of detections on both the real and imaginary parts of the complex monopulse output to efficiently computed, model estimations of the same. Multi-ping trends in beam-time space of the measured and modeled multipath echo differences will facilitate efficient corrections to the assumed sound speed structure and bathymetry via low order empirical and analytical parametric perturbations
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