Compressed sensing GNSS signal acquisition algorithm based on singular value decomposition

doi:10.7523/j.ucas.2021.0031

Abstract

Abstract: Signal acquisition is the key step of GNSS (global navigation satellite system) signal reception, and its search process is computationally expensive. Compressed sensing can reduce the amount of computation, but it has a certain impact on the acquisition performance. In order to improve the performance of compressed sensing acquisition algorithm, based on the sparsity of GNSS signal, a Gaussian measurement matrix based on singular value decomposition is constructed. Compared with the traditional Gaussian measurement matrix, the constructed measurement matrix has better performance of non-correlation and reconstruction. Simulation results show that compared with the traditional Gaussian compressed sensing acquisition algorithm, the acquisition probability of the improved algorithm is significantly improved in the case of lower signal-to-noise ratio.

Key words: GNSS, signal acquisition, compressed sensing, singular value decomposition

CLC Number:

TN927.23

DENG Lele, ZHOU Fangming, ZHAO Lulu, LIANG Guang, YU Jinpei. Compressed sensing GNSS signal acquisition algorithm based on singular value decomposition[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(1): 128-134.

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