Efficient tensor model‐Toeplitz matrix iterative reconstruction for angle estimation with nested array

• Published in: Electronics letters Vol. 59; no. 15
• Main Authors: Zhan, Chenghong, Hu, Guoping, Zhao, Fangzheng, Zhou, Hao
• Format: Journal Article
• Language: English
• Published: Stevenage John Wiley & Sons, Inc 01-08-2023; Wiley
• Subjects: Algorithms; array signal processing; Arrays; Covariance matrix; Data structures; Decomposition; Direction of arrival; Iterative methods; MIMO radar; Parameter estimation; radar; radar applications; radar detection; radar signal processing; radar tracking; Reconstruction; Signal processing; sonar and navigation; Tensors
• ISSN: 0013-5194; 1350-911X
• DOI: 10.1049/ell2.12912

This letter proposes an efficient tensor model for Direction of Departure (DOD) and Direction of Arrival (DOA) estimation based on bistatic nested Multiple‐Input Multiple‐Output (MIMO) radar. Tensor offers a robust solution in characterizing multi‐dimensional data structures, ensuring data integrity, and has demonstrated remarkable effectiveness in the realm of multi‐dimensional parameter estimation. However, the complexity of traditional methods for constructing tensors is a major obstacle to practical applications. In response, this research introduces a novel approach that utilizes an iterative two‐dimensional Toeplitz matrix reconstruction method to rapidly derive expanded virtual covariance matrices prior to tensor construction. This streamlines the algorithm and improves efficiency. Numerical simulations have verified the superiority of this algorithm.
1. The proposed approach utilizes Toeplitz matrix‐based quadratic reconstruction to address rank deficiency issues and obtain an equivalent virtual covariance matrix with minimal complexity.
2. Results demonstrate that this approach achieves reduced computational complexity while maintaining high estimation performance.