DOA Estimation of GNSS Signals Based on Deconvolved Conventional Beamforming

• Published in: Remote sensing (Basel, Switzerland) Vol. 16; no. 20; p. 3856
• Main Authors: Wu, Jian, Li, Chenglong, Lin, Honglei, Tang, Xiaomei, Wang, Feixue
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2024
• Subjects: Algorithms; Artificial satellites in navigation; Beamforming; Complexity; Deconvolution; deconvolved conventional beamforming; Direction of arrival; DOA estimation; Energy; Forecasts and trends; Global navigation satellite system; GNSS; Linear arrays; Methods; multipath; Neural networks; Optimization algorithms; Parameter estimation; Receivers & amplifiers; Satellites; Signal to noise ratio; Theoretical analysis; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs16203856

The Direction of Arrival (DOA) parameter is a key parameter in directional channel modeling for GNSS systems and multipath suppression. However, achieving high-precision, low-complexity DOA estimation of multiple signal sources without requiring a known source number is still a challenge. This paper introduces a satellite navigation DOA parameter estimation method based on deconvolution beamforming. By exploiting the translational invariance property of the uniform linear array pattern, the deconvolution process is applied to the de-spread array pattern of satellite navigation signals, achieving high-precision estimation of DOA parameters. This method can achieve high-precision blind DOA estimation of multiple signal sources while significantly reducing the estimation complexity. Compared with traditional methods, precise DOA estimation can be achieved even in low-signal-to-noise-ratio conditions and with a small number of elements in the array. The theoretical analysis and simulation results verify the effectiveness of the proposed algorithm.