Abstract
Synthetic aperture sonar (SAS) provides high-resolution acoustic imaging by processing coherently the backscattered acoustic signal recorded over consecutive pings. Traditionally, object detection and classification tasks rely on high-resolution seafloor mapping achieved with widebeam, broadband SAS systems. However, aspect- or frequency-specific information is crucial for improving the performance of automatic target recognition algorithms. For example, low frequencies can be partly transmitted through objects or penetrate the seafloor providing information about internal structure and buried objects, while multiple views provide information about the object's shape and dimensions. Sub-band and limited-view processing, though, degrades the SAS resolution. In this paper, SAS imaging is formulated as an ℓ1-norm regularized least-squares optimization problem which improves the resolution by promoting a parsimonious representation of the data. The optimization problem is solved in a distributed and computationally efficient way with an algorithm based on the alternating direction method of multipliers. The resulting SAS image is the consensus outcome of collaborative filtering of the data from each ping. The potential of the proposed method for high-resolution, narrowband, and limited-aspect SAS imaging is demonstrated with simulated and experimental data.
Highlights
Synthetic aperture sonar (SAS) combines coherently the backscattered echoes from successive acoustic pulses for high-resolution seafloor imaging with application in mine countermeasures, underwater archaeology, or inspection of underwater installations.1,2 an active sonar transmits a short pulse to insonify the seafloor and records the backscattered waves repeatedly while it moves along a predefined path to form a synthetic aperture
The crossrange resolution achieved with SAS systems is independent of frequency and range, i.e., it is not limited by the physical dimensions of a real aperture which is characterized by a constant angular resolution determined by its beampattern resulting in a range and frequency dependent cross-range resolution
The array displacement between pings is Dy 1⁄4 0:09 m and the cross-range distance from À2 to 2 m is used for aperture synthesis so that the whole imaging area is within the À3 dB beam width of the transmitter which is 40
Summary
Synthetic aperture sonar (SAS) combines coherently the backscattered echoes from successive acoustic pulses (pings) for high-resolution seafloor imaging with application in mine countermeasures, underwater archaeology, or inspection of underwater installations. an active sonar transmits a short pulse to insonify the seafloor and records the backscattered waves repeatedly while it moves along a predefined (usually linear) path to form a synthetic aperture. Synthetic aperture sonar (SAS) combines coherently the backscattered echoes from successive acoustic pulses (pings) for high-resolution seafloor imaging with application in mine countermeasures, underwater archaeology, or inspection of underwater installations.. SAS imaging refers to the inverse problem of reconstructing the seafloor reflectivity by coherently processing the recorded signals from the synthetic aperture. Utilizing widebeam systems and broadband pulses at a high ping repetition rate, synthetic aperture processing can achieve a centimetric range and cross-range resolution resulting in optical-like images of the seafloor reflectivity.. We formulate the SAS imaging problem within the compressive sensing (CS) framework, which asserts that underlying sparse signals can be reconstructed from very few measurements with convex optimization.. SAS imaging is formulated in the frequency domain, in Sec. IV, as a least-squares optimization problem regularized with an ‘1-norm penalty which promotes sparse solutions.. The reader is advised to consult the Appendix for a summary on the basic notions on convex optimization and the mathematical background of the ADMM algorithm
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