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Parallel simulation method of GNSS multipath signal based on GPU
Author(s) -
Xin Kang,
Rui Wang,
Zhicheng Lv,
Baiyu Li,
Weihua Mou
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1971/1/012070
Subject(s) - multipath propagation , computer science , gnss applications , multipath mitigation , bottleneck , signal (programming language) , filter (signal processing) , real time computing , delay spread , asynchronous communication , algorithm , parallel computing , global positioning system , channel (broadcasting) , embedded system , telecommunications , programming language , computer vision
In order to solve the problems of the traditional GNSS multipath signal simulation methods, such as the complexity increases linearly with the number of multipath signals, inconvenient parameter updating and long operation time, a GPU based GNSS multipath signal parallel simulation method is proposed. Based on Farrow variable fractional delay filter, an independent parallel computing model of multi-channel filter coefficients is established, and a large number of floating-point units in GPU are used for parallel computing and filtering. Aiming at the performance bottleneck of this method, the optimization strategy of asynchronous parallel execution is given. The computer simulation results show that the complexity and operation time of the proposed method will not increase with the increase of the number of multipath signals. For the GNSS direct signal with sampling rate of 75MHz and time length of 1s, the maximum time consuming of the proposed method to generate 50 ∼ 1000 multipath signals is 158.6ms. Compared with the method of serial simulation on CPU, the proposed method speeds up to about 9.5 times, and the real-time simulation of multipath signals in complex environment can be realized.

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