Wideband underwater sonar imaging via compressed sensing with scaling effect compensation

Abstract

By exploiting the sparsity of the imaging scene, compressed sensing (CS) imaging may provide an effective solution to cope with the tradeoff of high azimuth resolution and wide swath in synthetic aperture sonar imaging. However, existing CS imaging methods are based on narrowband signal model and the scaling effect on the echoes is normally omitted, which may seriously affect the ultimate image reconstruction performance. This paper establishes the wideband CS underwater sonar imaging model at first, where the scaling effect and Doppler frequency shift are jointly considered. Furthermore, two wideband CS imaging approaches are discussed in uniform scale-range space and velocity-range space, respectively. Besides, modified ℓ ₁-norm minimization algorithms are proposed for the scene reconstruction in velocity-range space. Finally, numerical experiments are provided to demonstrate the effectiveness of the proposed model and the reconstruction algorithms.

摘要

现有雷达和声纳压缩感知成像仅考虑目标回波的时延和多普勒效应, 忽略了高速目标回波的尺度伸缩效应, 限制了其在声呐成像中的应用。 针对宽幅高分合成孔径声呐(SAS)成像需求, 本文基于对水中场景稀疏性和高速目标宽带信号尺度效应分析, 提出了基于信号尺度效应补偿的水中目标压缩感知宽带成像理论和方法。 上述工作现有文献没有涉及, 本文工作丰富了现有压缩感知成像理论和应用。 本文主要创新点如下:

• 1. 基于宽带信号尺度伸缩效应分析和建模, 首次完整提出了基于水中目标单脉冲回波的宽带压缩感知成像新模型和新理论。

• 2. 分别提出了宽带压缩感知距离-速度和距离-尺度两种成像空间, 形成了水中目标宽带压缩感知成像的理论框架。

• 3. 基于相关度较高压缩矩阵对成像的影响, 针对距离-速度成像空间成像给出了改进的1范数最小化算法, 并提出了两种具体可行的实现方法。

• 4. 基于实际声呐平台参数和成像场景, 通过详细仿真试验验证了相关理论算法的有效性, 并证明其便于工程实现和推广应用。