Le Courtois Florent, Bonnel Julien
Lab-STICC (UMR CNRS 6285), ENSTA Bretagne (Université Européenne de Bretagne), 2 rue François Verny, 29806 Brest Cedex 9, France.
J Acoust Soc Am. 2015 Aug;138(2):575-83. doi: 10.1121/1.4926381.
In shallow water zones and at low frequency, seabed and water column properties can be estimated from the acoustic wavenumbers using inversion algorithms. When considering horizontal line arrays (HLA) and narrowband sources, the wavenumbers can be evaluated with classic spectral analysis methods. In this paper, a compressed sensing (CS) method for sparse recovery of the wavenumbers is proposed. This takes advantage of the few propagating modes and allows for spectral estimation when short HLA are used. The CS representation improves the wavenumber estimation, compared to the Fourier transform. However, for small arrays and several propagating modes, the CS generates interferences and does not allow proper wavenumber estimation. When considering broadband sources, it is possible to combine the wavenumbers estimated at several frequencies in order to build a frequency-wavenumber (f - k) representation. In this case, a post-processing tracking operation which improves the f - k resolution is presented. This relies on a general approach of waveguide physics and uses a particle filtering (PF) algorithm to track the wavenumbers. The consecutive use of CS and PF leads to a better wavenumber estimation. This methodology can be used for sources that are not at an end-fire position. It is illustrated by simulations and successfully applied on the Shallow Water 2006 data using the 32 sensor SHARK array.
在浅水区和低频条件下，可以使用反演算法从声波数估计海底和水柱特性。当考虑水平线列阵（HLA）和窄带声源时，波数可以用经典谱分析方法进行评估。本文提出了一种用于波数稀疏恢复的压缩感知（CS）方法。该方法利用了少数传播模式，并且在使用短HLA时能够进行谱估计。与傅里叶变换相比，CS表示改进了波数估计。然而，对于小阵列和几种传播模式，CS会产生干扰，无法进行正确的波数估计。当考虑宽带声源时，可以将在几个频率处估计的波数组合起来，以构建频率-波数（f-k）表示。在这种情况下，提出了一种提高f-k分辨率的后处理跟踪操作。这依赖于波导物理的一般方法，并使用粒子滤波（PF）算法来跟踪波数。连续使用CS和PF可实现更好的波数估计。该方法可用于不在端射位置的声源。通过模拟进行了说明，并使用32传感器SHARK阵列成功应用于2006年浅水数据。
