Direction-of-Arrival Estimation for 2D Coherently Distributed Sources with Nested Array Based on Matrix Reconstruction

Abstract

This paper has made proposition of a nested array and an estimation algorithm for direction-of-arrival (DOA) of two-dimensional (2D) coherently distributed (CD) sources. According to the difference coarray concept, double parallel hole-free virtual uniform linear arrays are generated by virtue of vectorization operation on cross-correlation matrices of subarrays. Sensor coordinates of virtual arrays are derived. Rational invariance relationships of virtual arrays are derived. According to the rotational invariance relationships, matrices satisfying rotation invariance are constructed by extracting and regrouping the receive vectors of the virtual arrays, and then an estimation of signal parameters via rotational invariance techniques- (ESPRIT-) like framework on matrix reconstruction is deduced. Optimal configuration of the nested array as well as computational complexity are analyzed. Without pair matching, the proposed method can resolve more sources than the sensor number. Simulation outcomes indicate that the proposed method tends to have a better performance as compared to the traditional uniform arrays that have similar number of sensors.

Parameter Estimation for Two-Dimensional Incoherently Distributed Source with Double Cross Arrays

“…Considering CD sources, scholars have presented estimators in [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. For 1D ID distributed sources, scholars have proposed various parameter estimation algorithms, mainly including subspace algorithms such as DSPE [ 1 ] and DSPARE [ 4 ], covariance matching estimation techniques [ 26 , 27 , 28 ], maximum likelihood estimation algorithms [ 29 , 30 , 31 , 32 ] and beamforming algorithms [ 33 , 34 , 35 ].…”