Detection and imaging performance of a synthetic aperture sonar

In this paper, we introduce a novel sub-bottom profiler, making good use of the Mills cross configuration of multibeam sonar and synthetic aperture techniques of the synthetic aperture sonar system. The receiver array is mounted along the ship keel, while the transmitter array is mounted perpendicular to the receiver array. With the synthetic aperture technique, the along-track resolution can be greatly improved. The system often suffers from motion error, which severely degrades the imaging performance. To solve this problem, the imaging algorithm with motion compensation (MC) is proposed. With the presented method, the motion error is first estimated based on overlapped elements between successive pulses. Then, the echo data is processed by using the range migration algorithm based on the phase center approximation (PCA) method, which simultaneously performs the MC with the estimated motion error. In order to validate the proposed sub-bottom profiler and data processing method, some simulations and lake trial results are discussed. The processing results of the real data further indicate that the presented configuration has great potential to find buried objects in seabed sediments.

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Compressive Underwater Sonar Imaging with Synthetic Aperture Processing

Remote Sensing ◽

10.3390/rs13101924 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1924

Author(s):

Ha-min Choi ◽

Hae-sang Yang ◽

Woo-jae Seong

Keyword(s):

Experimental Data ◽

Synthetic Aperture ◽

High Concentration ◽

Side Scan Sonar ◽

Synthetic Aperture Sonar ◽

Underwater Image ◽

Line Array ◽

High Level ◽

Imaging Algorithms ◽

Imaging Performance

Synthetic aperture sonar (SAS) is a technique that acquires an underwater image by synthesizing the signal received by the sonar as it moves. By forming a synthetic aperture, the sonar overcomes physical limitations and shows superior resolution when compared with use of a side-scan sonar, which is another technique for obtaining underwater images. Conventional SAS algorithms require a high concentration of sampling in the time and space domains according to Nyquist theory. Because conventional SAS algorithms go through matched filtering, side lobes are generated, resulting in deterioration of imaging performance. To overcome the shortcomings of conventional SAS algorithms, such as the low imaging performance and the requirement for high-level sampling, this paper proposes SAS algorithms applying compressive sensing (CS). SAS imaging algorithms applying CS were formulated for a single sensor and uniform line array and were verified through simulation and experimental data. The simulation showed better resolution than the ω-k algorithms, one of the representative conventional SAS algorithms, with minimal performance degradation by side lobes. The experimental data confirmed that the proposed method is superior and robust with respect to sensor loss.

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An Imaging Algorithm for Multireceiver Synthetic Aperture Sonar

Remote Sensing ◽

10.3390/rs11060672 ◽

2019 ◽

Vol 11 (6) ◽

pp. 672 ◽

Cited By ~ 3

Author(s):

Xuebo Zhang ◽

Cheng Tan ◽

Wenwei Ying

Keyword(s):

Frequency Domain ◽

Evaluation Method ◽

Real Data ◽

Synthetic Aperture ◽

Reference Spectrum ◽

Coupling Term ◽

Imaging Algorithm ◽

Synthetic Aperture Sonar ◽

The Difference ◽

Imaging Performance

For the multireceiver synthetic aperture sonar (SAS), the point target reference spectrum (PTRS) in the two-dimensional (2D) frequency domain and azimuth modulation in the range Doppler domain were first deduced based on a numerical evaluation method and accurate time delay. Then, the difference between the PTRS and azimuth modulation generated the coupling term in the 2D frequency domain. Compared with traditional methods, the PTRS, azimuth modulation and coupling term was better at avoiding approximations. Based on three functions, an imaging algorithm is presented in this paper. Considering the fact that the coupling term is characterized by range variance, the range-dependent sub-block processing method was exploited to perform the decoupling. Simulation results showed that the presented method improved the imaging performance across the whole swath in comparison with existing multireceiver SAS processor. Furthermore, real data was used to validate the presented method.

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