Synthetic aperture image enhancement with near-coinciding Nonuniform sampling case

IF 4 3区 计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Computers & Electrical Engineering Pub Date : 2024-10-25 DOI:10.1016/j.compeleceng.2024.109818
Xuebo Zhang , Peixuan Yang , Dengyu Cao
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Abstract

Multireceiver synthetic aperture sonar (SAS) uses multiple receivers to collect echoed signals, leading to nonuniform sampling in the azimuth dimension if the moving distance between adjacent pings is not half the receiver array length. The filter bank reconstruction (FBR) method, based on matrix inversion, is commonly used to address this by reconstructing uniform data from nonuniform signals. However, in practice, near-coinciding sampling can occur due to inaccuracies in the towed velocity of the SAS system, influenced by ocean conditions. The signal correlation of these near-coinciding receivers is very strong, and thus the steering vectors corresponding to these receivers are not completely independent. This further leads to an ill-conditioned system transfer function matrix made up of the receiver steering vectors, and results in inaccurate calculations of inverse matrix. Consequently, the FBR method suffers from significant signal-to-noise ratio loss or fails to reconstruct uniform signals accurately. This degradation in signal quality directly impacts the accuracy of target reconstruction, leading to errors in identifying and locating targets. This paper quantitatively defines nonuniform sampling with near-coinciding samples and discusses performance loss in various cases. To enhance imaging performance, we propose a method for reconstructing uniform signals. Simulation results demonstrate that the proposed method outperforms the conventional FBR method, providing better target reconstruction and higher efficiency.
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合成孔径图像增强与近乎吻合 非均匀采样情况
多接收器合成孔径声纳(SAS)使用多个接收器收集回波信号,如果相邻 pings 之间的移动距离不是接收器阵列长度的一半,就会导致方位维度的不均匀采样。基于矩阵反演的滤波器组重建(FBR)方法通常用于解决这一问题,即从非均匀信号中重建均匀数据。然而,在实际应用中,由于 SAS 系统的拖曳速度受海洋条件影响而存在误差,可能会出现近重合采样的情况。这些近重合接收器的信号相关性非常强,因此这些接收器对应的转向矢量并非完全独立。这进一步导致由接收器转向矢量组成的系统传递函数矩阵条件不佳,并导致逆矩阵计算不准确。因此,FBR 方法会出现明显的信噪比损失,或无法准确重建均匀信号。信号质量的下降直接影响目标重建的准确性,导致目标识别和定位错误。本文定量定义了近重合采样的非均匀采样,并讨论了各种情况下的性能损失。为了提高成像性能,我们提出了一种重建均匀信号的方法。仿真结果表明,所提出的方法优于传统的 FBR 方法,能提供更好的目标重建和更高的效率。
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来源期刊
Computers & Electrical Engineering
Computers & Electrical Engineering 工程技术-工程:电子与电气
CiteScore
9.20
自引率
7.00%
发文量
661
审稿时长
47 days
期刊介绍: The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency. Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.
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