An adaptive weighted spatial smoothing algorithm utilizing virtual beamforming

With the existence of multipath interferences or smart jamming, the desired signal is correlated or even coherent with interferences in an adaptive array. The array performance is severely degraded when the desired signal is highly correlated or coherent with some of the interferences. The performance degradation is commonly called the desired signal cancellation phenomenon, which can be explicitly interpreted in the framework of generalized sidelobe canceller (GSC). Spatial smoothing (SS) was proposed to overcome the array performance degradation in the coherent environment, however, the subarray averaging in SS leads to the array aperture loss. Moreover, spatial smoothing can´t decorrelate the desired signal and interferences completely, especially in some angles of the arrivals. In this paper, an adaptive weighted spatial smoothing (AWSS) technique is proposed. Based on the analysis of the correlation matrix of the weighted spatial smoothing, a virtual adaptive beamforming problem is constructed to compute the sliding weight. The correlation coefficients of the desired signal and the interferences in the after-weighted correlation matrix are approximately equal to zeros, due to the s of the virtual beamforming. The theoretical analysis and simulation results show that the AWSS algorithm can decorrelate the desired signal and the coherent interferences more efficiently. The number of subarrays needed decreases, and the array aperture loss is reduced in spatial smoothing.