A Direction-Of-Arrival Estimation Algorithm Based On Spatial Translation for Coherent Signals
Yaofeng Tang, Yuhang Chen, Kuangang Fan, Tong Bie · 2022
To solve the problem of coherent signal detection, this paper proposes an eigenvector direction-of-arrival(DOA) estimation algorithm based on the invariant characteristics of spatial translation. Firstly, we use linear prediction theory to obtain polynomials containing signal information, and then construct toeplitz matrix and establish the relationship between toeplitz matrix and signal space. Furthermore, the problem is transformed into solving linear equations, and then the dimension of linear equations is increased by spatial translation. Moreover, the linear equations are solved by weighted least squares(WLS). Finally, the maximum likelihood(ML) rule is used to select DOA. Simulation results show that compared with existing algorithms, the proposed algorithm can process coherent signals with lower errors and higher resolution even under signal-to-noise ratio(SNR) is low and/or snapshot number is small. In certain conditions, the resolution of the proposed algorithm can reach 95%.