Enhanced root-MUSIC for coherent signals with multi-resolution composite arrays
Aihua Liu, Xin Zhang, Jiazhi Zhang, Qiang Yang · 2019
In this paper, an enhanced approach using multi-resolution composite arrays (MRCA) is proposed to deal with coherent signals. To decorrelate the coherency of signals, the proposed method operates on the sparse uniform linear subarrays (SULSAs) of the MRCA by using the forward-backward spatial smoothing (FBSS) technique. After that, the root-multiple signal classification (root-MUSIC) algorithm is applied to each SULSA of the MRCA. For each DOA, multiple roots exist in the polynomial of root-MUSIC for SULSA due to spatial aliasing, which are proven to have uniformly distributed phases. By finding the phase of an arbitrary root, the phases of the other roots can be calculated. Then, the genuine DOAs are obtained by intersecting the roots of all the SULSAs. To match these common roots, an effective root matching processing is proposed. Simulation results demonstrate the efficiency of the proposed algorithm.