Joint Angle and Frequency Estimation in Linear Arrays Based on Covariance Reconstruction and ESPRIT

Abstract

Joint angle and frequency estimation, one of the key technologies in wireless communication and radar science, has been extensively studied by scholars. For linear arrays, this paper proposes a joint angle and frequency estimation method based on covariance reconstruction and the estimation of signal parameters via rotational invariance techniques (CR-ESPRIT). We first use the received conjugate signal to reconstruct a covariance matrix. Then, we use the least squares-ESPRIT (LS-ESPRIT) algorithm to estimate the desired frequencies. Finally, we estimate the angles according to the reconstructed matrix. The proposed method can estimate signal parameters via automatic pairing and without an additional parameter pairing process under the condition of a uniform or a nonuniform array. Moreover, this method has high estimation accuracy, excellent and stable anti-noise performance, and strong algorithmic robustness. Through a computer simulation analysis, we can confirm the reliability and validity of the proposed parameter estimation method. A comparison with other methods further proves the performance advantages of the developed method. The method in this paper can be easily applied to many signal processing contexts, such as electronic reconnaissance and wireless communication.