The objective of this work is to estimate the Direction of Arrival (DOA) of signals from multiple closely spaced non-Gaussian sources corrupted by additive Gaussian noise. Generally, this is achieved by using higher order statistics (HoS) based MUSIC spectrum. In HoS, the Fourth order Cumulant is utilized because of its property of insensitivity to Gaussian process. But in the case of resolving closely spaced sources, a large number of sensor elements are required; otherwise, the resolution gets deteriorated. The large number of sensor elements leads to high computational burden. We propose a computationally efficient modified Spectrum that combines Fourth order Cumulants based MUSIC spectrum and its second-order differential counterparts. The proposed spectrum for DOA estimation offers good statistical performance and better accuracy the existing methods even in the case of extremely closely spaced signal sources. The improvement in the aspects of resolution and accuracy is substantiated by means of various simulation results such as Monte-Carlo simulations, spectral width, resolution with respect to angular separation, and comparison of RMSE with respect to number of array elements, number of snapshots, and SNR. The computational complexity analysis of the proposed method is also presented.
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