Subspace array processing using spatial time-frequency distributions: Applications for denoising structural echoes of elastic targets

Abstract

Structural echoes of underwater elastic targets, used for detection and classification purposes, can be highly localized in the time-frequency domain and can be aspect-dependent. Hence such structural echoes recorded along a distributed (synthetic) aperture, e.g., using a moving receiver platform, would not meet the stationarity and multiple snapshots requirements of common subspace array processing methods used for denoising array data based on their estimated covariance matrix. To address this issue, this article introduces a subspace array processing method based on the space-time-frequency distribution (STFD) of single-snapshots of non-stationary signals. This STFD is obtained by computing Cohen's class time-frequency distributions between all pairwise combination of the recorded signals along an arbitrary aperture array. This STFD is interpreted as a generalized array covariance matrix which automatically accounts for the inherent coherence across the time-frequency plane of the received nonstationary echoes emanating from the same target. Hence, identifying the signal's subspace from the eigenstructure of this STFD provides a means for denoising these non-stationary structural echoes by spreading the clutter and noise power in the time-frequency domain; as demonstrated here numerically and experimentally using the structural echoes of a thin steel spherical shell measured along a synthetic aperture.