Low Complexity Super-Resolution Wideband DOA Estimation for LFM Signals Using FFT Dechirp Algorithm with a Few Snapshots

• Published in: Circuits, systems, and signal processing Vol. 42; no. 11; pp. 6591 - 6613
• Main Authors: Partovi Sangi, Abbas, Jamali, Jasem, Fatehi-Dindarlou, Mohammad Hossein, Ghanbarian, Mohammad Mehdi
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-11-2023; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Broadband; Circuits and Systems; Complexity; Direction of arrival; Electrical Engineering; Electronics and Microelectronics; Engineering; Estimation; Fast Fourier transformations; Fourier transforms; Frequency modulation; Instrumentation; Iterative methods; Linear arrays; Signal,Image and Speech Processing; AMV; LFM signals; ULA; LSPICE; Dechirp algorithm; FFT transform
• ISSN: 0278-081X; 1531-5878
• DOI: 10.1007/s00034-023-02403-5

Wideband linear frequency modulation (LFM) signals are widely used in radar, sonar, mobile, and similar applications. One of the common problems of algorithms for estimating the direction of arrival (DOA) of LFM signals is that the number of snapshots must be large for good estimation. Therefore, they are not suitable for real-time and low-power applications. In this paper, we proposed a method of estimating DOA based on the sparse iterative covariance (SPICE) algorithm, which has features such as low computational complexity for the uniform linear array (ULA) using the Fourier transform (FFT). We first developed the dechirp process for linear frequency modulation signals using the Fourier transform. Then we modified the SPICE algorithm for linear arrays. Finally, we have obtained the calculation of the DOA estimation for a few snapshots with low computational complexity and high resolution. Compared to other methods, the simulation results of the proposed LSPICE algorithm show an increase in estimation accuracy, higher resolution, more acceptable accuracy in low SNRs, less error in high SNRs, favorable response with low snapshots, and lower computational complexity.