SYSTEM AND METHOD FOR HYBRID MINIMUM MEAN SQUARED ERROR MATRIX-PENCIL SEPARATION WEIGHTS FOR BLIND SOURCE SEPARATION

摘要

A technique for blind source separation (BSS') of statistically independent signals (1001) with low signal-to-noise plus interference ratios under a narrowband assumption utilizing cumulants (1002)in conjunction with spectral estimation of the signal subspace (1007) to perform the blind separation (1005) is disclosed. The BSS technique utilizes a higher-order statistical method, specifically fourth-order cumulants (1002), with the generalized eigen analysis of a matrix-pencil (1003) to blindly separate a linear mixture of unknown, statistically independent, stationary narrowband signals (1001) at a low signal-to-noise plus interference ratio having the capability to separate signals in spatially and/or temporally correlated Gaussian noise. The disclosed BSS technique separates low-SNR co-channel sources for observations using an arbitrary un-calibrated sensor array (1001). The disclosed BSS technique forms a separation matrix (1004) with hybrid matrix-pencil adaptive array weights (1003) that minimize the mean squared errors due to both interference emitters and Gaussian noise. The hybrid weights (1003) maximize the signal-to interference-plus noise ratio.