An Improved Music Algorithm Based on One-Bit Datas : One-Bit MMUSIC
Yanliang Xiong, Jieming Shi, Huiyong Li, Ziyang Cheng · 2024
In this paper, we consider the problem of direction of arrival(DOA) estimation with one-bit quantized datas. Based on the existing one-bit multiple signal classification(MUSIC) algorithm, this paper gets datas form a uniform rectangular array(URA) then lets datas quantized by one-bit Analog to Digital Converters(ADCs) and introduces a switching matrix. The covariance matrix of one-bit datas is reconstructed by conjugation and product with the switching matrix, and then added to itself to obtain a new one-bit covariance matrix. This paper proposes an improved MUSIC algorithm based on the new covariance matrix, which is the one-bit modified multiple signal classification(MMUSIC) algorithm, and proves in simulation that when the number of snapshots is small, the signal-to-noise ratio is small, and the number of arrays is appropriate, the angle measurement performance of the one-bit MMUSIC algorithm is better than the existing one-bit MU-SIC algorithm, and the Cramer-Rao Bound(CRB) is given as a reference lower bound for the angle measurement performance.