scholarly journals An Imaging Algorithm for Multireceiver Synthetic Aperture Sonar

2019 ◽  
Vol 11 (6) ◽  
pp. 672 ◽  
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.

scholarly journals A Novel Sub-Bottom Profiler and Signal Processor

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5052
Author(s):  
Tan ◽  
Zhang ◽  
Yang ◽  
Sun
Keyword(s):  
Real Data ◽  
Synthetic Aperture ◽  
Motion Error ◽  
Buried Objects ◽  
Synthetic Aperture Sonar ◽  
Receiver Array ◽  
Sonar System ◽  
Data Processing Method ◽  
Imaging Performance ◽  
Along Track

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.

scholarly journals Frequency Domain Panoramic Imaging Algorithm for Ground-Based ArcSAR

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7027
Author(s):  
Yun Lin ◽  
Yutong Liu ◽  
Yanping Wang ◽  
Shengbo Ye ◽  
Yuan Zhang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Frequency Domain ◽  
Matched Filter ◽  
Deformation Monitoring ◽  
Polar Coordinates ◽  
Fast Imaging ◽  
Synthetic Aperture ◽  
Imaging Algorithm ◽  
Imaging Algorithms ◽  
Aperture Radar

The ground-based arc-scanning synthetic aperture radar (ArcSAR) is capable of 360° scanning of the surroundings with the antenna fixed on a rotating arm. ArcSAR has much wider field of view when compared with conventional ground-based synthetic aperture radar (GBSAR) scanning on a linear rail. It has already been used in deformation monitoring applications. This paper mainly focuses on the accurate and fast imaging algorithms for ArcSAR. The curvature track makes the image focusing challenging and, in the classical frequency domain, fast imaging algorithms that are designed for linear rail SAR cannot be readily applied. This paper proposed an efficient frequency domain imaging algorithm for ArcSAR. The proposed algorithm takes advantage of the angular shift-invariant property of the ArcSAR signal, and it deduces the accurate matched filter in the angular-frequency domain, so panoramic images in polar coordinates with wide swath can be obtained at one time without segmenting strategy. When compared with existing ArcSAR frequency domain algorithms, the proposed algorithm is more accurate and efficient, because it has neither far range nor narrow beam antenna restrictions. The proposed method is validated by both simulation and real data. The results show that our algorithm brings the quality of image close to the time domain back-projection (BP) algorithm at a processing efficiency about two orders of magnitude better, and it has better image quality than the existing frequency domain Lee’s algorithm at a comparable processing speed.

scholarly journals Compressive Underwater Sonar Imaging with Synthetic Aperture Processing

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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