Focusing late-time returns from elastic targets in bistatic collection geometries

Targets encountered during synthetic aperture sonar (SAS) surveys may exhibit elastic scattering behavior and re-radiate sound after initial interrogation. These re-radiated returns are often described as “late-time” energy, as they reach the sonar after the initial geometric returns. Range-specific focusing methods can enhance acoustic features such as late-time energy, but these methods typically make a monostatic sonar approximation that may not hold in very shallow water sensing geometries. This presentation will discuss the development of a late-time reconstruction algorithm applicable to bistatic sonar geometries. Using both simulated and experimental sonar data from monostatic and bistatic collection geometries, this work will first quantify the differences between traditionally beamformed imagery and late-time-focused imagery using common image quality metrics. Next, we will quantitatively compare the impact of collection geometry on the performance of late-time focusing algorithms. Finally, the work will describe methods that use information from a multi-static collection to compress late-time energy down to a high-contrast, spatiallycondensed point. The analysis of these signal processing strategies will focus on their potential applications to automatic target recognition.