Iterative Adaptive Approach for wide-band active sonar array processing

Zhaofu Chen, Jian Li, P. Stoica, K. Lo
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引用次数: 7

Abstract

Sector scan sonars can be used for detection and identification of man-made objects located on the sea floor. Wide-band acoustic signals are employed in this kind of sonar system to enhance range resolution. The conventional delay-and-sum beamformer (CBF) produces sonar images with high sidelobe levels and poor angular resolution. Adaptive beamforming algorithms together with spatial resampling can be applied to mitigate this problem. The algorithm “Spatial Processing: Optimized and Constrained” (SPOC), used in a recent work, is studied herein and shown to be identical to the basic form of the FOCal Underdetermined System Solver (FOCUSS) algorithm. A recently developed algorithm, the Iterative Adaptive Approach (IAA), is proposed for this sonar application and various implementation issues are discussed. Experimental results show that the IAA algorithm produces better sonar images than the CBF and Minimum Variance Distortionless Response (MVDR) algorithms in terms of sidelobe suppression and angular resolution. Compared with SPOC, IAA provides clearer acoustic highlights of the imaged object and a higher density of pixels representing the object.
宽带主动声呐阵处理的迭代自适应方法
扇形扫描声纳可用于探测和识别位于海底的人造物体。这种声纳系统采用宽带声信号来提高距离分辨率。传统的延迟和波束形成器(CBF)产生的声纳图像副瓣电平高,角分辨率差。自适应波束形成算法结合空间重采样可以缓解这一问题。本文研究了最近一项工作中使用的“空间处理:优化和约束”(SPOC)算法,并证明该算法与FOCal欠定系统求解器(FOCUSS)算法的基本形式相同。针对这种声纳应用,提出了一种最新开发的算法迭代自适应方法(IAA),并讨论了各种实现问题。实验结果表明,IAA算法在旁瓣抑制和角分辨率方面优于CBF和最小方差无失真响应(MVDR)算法。与SPOC相比,IAA提供了更清晰的成像物体的声学亮点和更高密度的代表物体的像素。
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