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Underwater acoustic azimuth and elevation angle estimation using spatial invariance of two identically oriented vector hydrophones at unknown locations in impulsive noise

机译:使用两个相同方向的矢量水听器在脉冲噪声中未知位置的空间不变性来估计水下声方位角和仰角

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This paper proposes a new underwater acoustic 2-D direction finding algorithm using two identically oriented vector hydrophones at unknown locations in non-Gaussian impulsive noise. The two applied vector hydrophones are four-component, orienting identically in space with arbitrarily and possibly unknown displacement. Each vector hydrophone has three spatially co-located but orthogonally oriented velocity hydrophones plus another pressure hydrophone. The proposed algorithm employs the spatial invariance between the two vector hydrophones, but requires no a priori information of vector hydrophones' spatial factors and impinging sources' temporal forms. We apply ESPRIT to estimate vector hydrophones manifold and then to pair the x-axis direction cosines with y-axis direction cosines automatically and yield azimuth and elevation angle estimates. We also consider the additive noise be non-Gaussian impulsive, which is often encountered in underwater acoustics applications. Two typical impulsive noise model, Gaussian-mixture noise and symmetric α-stable (SαS) noise models are adopted. Instead of using conventional second order correlation of array output data, we define the vector hydrophone array sign covariance matrix (VSCM) for Gaussian-mixture noise and vector hydrophone array fractional lower order moment (VFLOM) matrix for SαS noise with 1 < α ≤ 2. These defined matrices may readily substitute customary vector hydrophone array covariance matrix for 2-D direction finding in impulsive noise.
机译:本文提出了一种新的水下声学二维测向算法,该算法在非高斯脉冲噪声中的未知位置使用两个相同方向的矢量水听器。所应用的两个矢量水听器是四分量的,在空间中相同地定向,具有任意且可能未知的位移。每个矢量水听器都具有三个在空间上位于同一位置但正交的速度水听器,再加上另一个压力水听器。该算法利用了两个矢量水听器之间的空间不变性,但是不需要矢量水听器的空间因素和撞击源的时间形式的先验信息。我们应用ESPRIT来估计矢量水听器歧管,然后自动将x轴方向的余弦与y轴方向的余弦配对,并得出方位角和仰角估计值。我们还认为加性噪声是非高斯脉冲的,这在水下声学应用中经常遇到。采用了两种典型的脉冲噪声模型:高斯混合噪声模型和对称α稳定(SαS)噪声模型。代替使用阵列输出数据的常规二阶相关性,我们定义用于高斯混合噪声的矢量水听器阵列符号协方差矩阵(VSCM)和用于1 <α≤2的SαS噪声的矢量水听器阵列分数低阶矩(VFLOM)矩阵这些定义的矩阵可以容易地用常规的矢量水听器阵列协方差矩阵代替脉冲噪声中的二维方向寻找。

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