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

作者：He Jin^*; Liu Zhong

来源：Digital Signal Processing, 2009, 19(3): 452-462.

DOI：10.1016/j.dsp.2007.10.012

• Array signal processing
• Direction-of-arrival estimation
• Vector hydrophone
• ESPRIT
• Impulsive noise
• Gaussian-mixture noise
• Symmetric alpha-stable noise
• Sign covariance matrix
• Fractional lower order moment

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 alpha-stable (S alpha S) 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 S alpha S noise with 1 < alpha <= 2. These defined matrices may readily substitute customary vector hydrophone array covariance matrix for 2-D direction finding in impulsive noise.

• 出版日期2009-5
• 单位南京理工大学