A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler

Na Xia,Yunqing Hong,Huazheng Du,Qinan Zhi,Menghua He

doi:10.1177/1550147720929620

Abstract

In various applications of satellite navigation and positioning, it is a key topic to select suitable satellites for positioning solutions to reduce the computational burden of the receiver in satellite selection system. Moreover, in order to reduce the processing burden of receivers, the satellite selection algorithm based on Gibbs sampler is proposed. First, the visible satellites are randomly sampled and divided into a group. The group is regarded as an initial combination selection scheme. Then, the geometric dilution of precision is chosen as an objective function to evaluate the scheme’s quality. In addition, the scheme is updated by the conditional probability distribution model of the Gibbs sampler algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. Furthermore, an “adaptive perturbation” strategy is introduced to improve the global searching ability of the algorithm. Finally, the extensive experimental results demonstrate that when the number of selected satellite is more than 6, the time that the proposed algorithm with the improvement of “adaptive perturbation” takes to select satellite once is 43.7% of the time that the primitive Gibbs sampler algorithm takes. And its solutions are always 0.1 smaller than the related algorithms in geometric dilution of precision value. Therefore, the proposed algorithm can be considered as a promising candidate for satellite navigation application systems.

Highlights

The BeiDou navigation satellite system (BDS) is a new system that provides positioning, navigation, and timing services for the entire Asia Pacific region since 2012, and the ultimate goal is to be used globally in 2020.1 As it is widely used, its service demand will increase
The details of Gibbs sampler algorithm to solve the satellite selection problem are described in section ‘‘Using improved Gibbs sampler algorithm to select optimal BeiDou satellite combination.’’ The experimental results are described in section ‘‘Experiment,’’ and the statistics and analysis are obtained from the amount of experimental data
According to simulation experiments on the algorithm, the results are as follows: (1) When the number of selected satellite is 6, the time that the proposed algorithm with the improvement of ‘‘adaptive perturbation’’ takes to select satellite once is 4.425 s, 43.7% of the BeiDou satellite has been widely used in the navigation and positioning of aircraft, ships and vehicles, time service, and other fields

Summary

Introduction

The BeiDou navigation satellite system (BDS) is a new system that provides positioning, navigation, and timing services for the entire Asia Pacific region since 2012, and the ultimate goal is to be used globally in 2020.1 As it is widely used, its service demand will increase. For the traditional algorithms,[7] the amount of calculation increases significantly with the increase in the number of observable satellites.[8] Furtherly, the largest tetrahedron volume algorithm, and the maximum orthogonal projection are mainly used for exactly four-satellite subset selection. These algorithms are usually not applied to engineering projects directly. The details of Gibbs sampler algorithm to solve the satellite selection problem are described in section ‘‘Using improved Gibbs sampler algorithm to select optimal BeiDou satellite combination.’’ The experimental results are described in section ‘‘Experiment,’’ and the statistics and analysis are obtained from the amount of experimental data. The summary and conclusion of this article are described in section ‘‘Conclusion.’’ The future scope of this article is described in section ‘‘Future scope.’’

Related work

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Findings

Conclusion