Robust Global Satellite Navigation System Positioning for Kernel Density Estimation in Non-Line-Of-Sight Environment

JIA Qiongqiong; ZHOU Yueying

doi:10.11999/JEIT231421

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JIA Qiongqiong, ZHOU Yueying. Robust Global Satellite Navigation System Positioning for Kernel Density Estimation in Non-Line-Of-Sight Environment[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231421

Citation:

JIA Qiongqiong, ZHOU Yueying. Robust Global Satellite Navigation System Positioning for Kernel Density Estimation in Non-Line-Of-Sight Environment[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231421

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Robust Global Satellite Navigation System Positioning for Kernel Density Estimation in Non-Line-Of-Sight Environment

doi: 10.11999/JEIT231421

JIA Qiongqiong^,,
ZHOU Yueying

Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China

Funds: The National Natural Science Foundation of China (U2133204), The Key Laboratory of Wide-Area Monitoring and Security Control Technology of Civil Aviation University of China Opened Foundation (202202)

Received Date: 2023-12-25
Rev Recd Date: 2024-05-19

Available Online: 2024-05-28

Abstract

Abstract

Non-Line-Of-Sight (NLOS) propagation will cause the pseudo-range measurement error of the Global Navigation Satellite System (GNSS) receivers, and eventually lead to a large positioning error, which is especially prominent in complex environments such as urban canyons. To solve this problem, a robust positioning method for Kernel Density Estimation (KDE) is proposed. The core idea is to introduce robust estimation theory into localization solution to alleviate the influence of NLOS. Considering that the pseudo-range observation error caused by NLOS deviates from the Gaussian distribution, the proposed method firstly uses the method based on KDE to estimate the probability density function of the observation error, and then uses the probability density function to construct a robust cost function for positioning solution, so as to alleviate the positioning error caused by NLOS. The experimental results show that the proposed method can effectively reduce GNSS positioning error in NLOS propagation environment.

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References(28)

References

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