Joint estimation for DOA and polarization parameters of orthogonal dipole array based on compressive sensing

Abstract

Objectives In terms of the arrival (DOA) estimation algorithm of traditional polarization sensitive array that has problems of high computation complexity and poor real-time performance, an orthogonal dipole polarization sensitive array structure based on compression sensing is proposed. Methods By applying the data compression technology to the system design, the proposed structure compresses the dimension of the receiving signal vector, controls the complexity of the system by reducing the number of front-end chains, and also brings high flexibility to the array structure design. At the same time, the dimensionality reduction-based multiple signal classification (MUSIC) algorithm is also proposed. First, the DOA estimation of signals is realized through spatial spectrum searching. Then, the Lagrange multiplier method is used to reduce the searching dimensionality and signal polarization parameters are obtained by solving the optimization problem. Results Simulation experiments show that the structure and algorithm proposed can obtain correct DOAs and polarization parameter estimations when the incident signals are completely polarized and incoherent. When the signal-noise ratio(SNR) is greater than 10 dB, the root mean square error（RMSE）of elevation angle is less than 0.05°. Conclusions Compared with the non-compressed structure with equal channel number under the same conditions, higher estimation accuracy and lower computational complexity can be obtained by utilizing the proposed structure.