Dominant-mode steered linear prediction for high resolution broadband source location
The authors develop a linear predictive approach for high-resolution broadband bearing estimation in low signal-to-noise ratio environments. The proposed technique is based on a space-time statistic called the steered covariance matrix (STCM). In broadband settings, the STCM has an advantage over the well-known cross-spectral density matrix in that it can be estimated with much greater statistical stability. In the present work, the STCM is used in conjunction with linear predictive spectral estimation and dominant-mode enhancement to obtain a broadband spatial spectral estimate with lower mean-square bearing estimation error than both incoherent MUSIC and a dominant-mode STCM-based minimum variance method in low signal-to-noise ratio simulation experiments.
