Simplified spatial smoothing for DOA estimation of coherent signals
Résumé
In coherent direction of arrival (DOA) estimation,subspace-based methods suffer from performance deteriorationbecause of the rank loss of the signal covariance matrix. Avariety of spatial smoothing preprocessing techniques have beenproposed for decorrelation, among which the enhanced spatialsmoothing preprocessing (ESS) technique shows outstandingperformance by exploiting the signal subspace. However, ESSis applied by squaring the matrix whose columns span thesignal subspace (called signal matrix), which involves unnecessarycomputational loads. Besides, the smoothed covariance matrixafter ESS is a linear combination of the sub-matrices of signalmatrix, where the coefficients of the combination may underminethe decorrelation performance. In this context, a simplifiedspatial smoothing (SSS) technique is proposed for decorrelationby averaging the sub-matrices of the signal matrix directly,and avoids redundant operations in squared signal matrix. Theproposed method is tested numerically in terms of the signal-to-noise ratio (SNR), the number of snapshots, angle separation,and the execution time. Simulation results show the improvementof the decorrelation performance, efficiency, and robustness withthe proposed method in coherent scenarios, compared with theother spatial smoothing preprocessing based methods.