Determining biosonar images using sparse representations
Determining biosonar images using sparse representations
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DOI：
10.1121/1.3101485
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发表时间：
2009-05-01
影响因子：
2.4
通讯作者：
Peremans, Herbert
中科院分区：
文献类型：
--
作者：
Fontaine, Bertrand;Peremans, Herbert
回声定位蝙蝠被认为能够通过发射脉冲和分析反射的回声来创造环境的图像。本文将稀疏表示理论及其在压缩感知中的进一步发展应用于生物声纳图像生成任务。考虑到目标图像表示是稀疏的，可以将该逆问题表述为一个凸优化问题，并且已经建立了定义良好且有效的求解方法。将得到的技术称为l1最小化，并将其应用于模拟数据，分析其相对于延迟精度和延迟分辨率实验的性能。在延迟精度实验中，该方法的性能可与相干接收机相媲美，对噪声具有较强的鲁棒性，并能重建由多个不同反射强度的紧密间隔反射器产生的复杂目标脉冲响应。同样的技术，除了重建生物声纳目标图像外，还可以通过解释蝙蝠头部相关传递函数诱导的位置线索来同时定位这些复杂的目标。最后，从l1 -最小化方法重构的目标图像的性质出发，对具体的蝙蝠行为实验进行了尝试性的解释。(C) 2009美国声学学会。(DOI: 10.1121/1.3101485)
Echolocating bats are thought to be able to create an image of their environment by emitting pulses and analyzing the reflected echoes. In this paper, the theory of sparse representations and its more recent further development into compressed sensing are applied to this biosonar image formation task. Considering the target image representation as sparse allows formulation of this inverse problem as a convex optimization problem for which well defined and efficient solution methods have been established. The resulting technique, referred to as L1-minimization, is applied to simulated data to analyze its performance relative to delay accuracy and delay resolution experiments. This method performs comparably to the coherent receiver for the delay accuracy experiments, is quite robust to noise, and can reconstruct complex target impulse responses as generated by many closely spaced reflectors with different reflection strengths. This same technique, in addition to reconstructing biosonar target images, can be used to simultaneously localize these complex targets by interpreting location cues induced by the bat's head related transfer function. Finally, a tentative explanation is proposed for specific bat behavioral experiments in terms of the properties of target images as reconstructed by the L1-minimization method. (C) 2009 Acoustical Society of America. [DOI: 10.1121/1.3101485]