Sequence Comparison in Reconstruction and Targeting in Underwater Sonar Imaging

I. Stanković, C. Ioana, M. Daković
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引用次数: 4

Abstract

An analysis of different sequences for the reconstruction and targeting of underwater sonar images is presented. The sonar images are assumed to be sparse, and their reconstruction is possible by using the compressive sensing theory. The goal is to localize and reconstruct targets by using an iterative version of the orthogonal matching pursuit (OMP) method. The sequences which are used as the transmitted signal waveforms are formed with: the Alltop sequence, the M sequence, a random Gaussian sequence, a binary random sequence, the Zadoff-Chu sequence, and the Bjorck sequence. The comparison of the reconstruction results is done for various numbers of samples in the sequences and sparsity levels. An analysis of the performance for each of the sequences in various noise levels is done as well. Percentage of successfully detected targets is used as a performance measure.
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水下声纳成像重建与瞄准中的序列比较
分析了用于水下声纳图像重建和定位的不同序列。假设声呐图像是稀疏的,利用压缩感知理论对其进行重构是可能的。目标是使用正交匹配追踪(OMP)方法的迭代版本来定位和重建目标。作为传输信号波形的序列有:Alltop序列、M序列、随机高斯序列、二进制随机序列、Zadoff-Chu序列和Bjorck序列。在序列和稀疏度不同的情况下,对重构结果进行了比较。分析了每个序列在不同噪声水平下的性能。成功检测目标的百分比用作性能度量。
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