An Improved PSO Algorithm and Its Application in GNSS Ambiguity Resolution
Source abstract
Abstract
In this study, we proposed a novel method for global navigation satellite system (GNSS) ambiguity resolution (AR). The proposed method utilizes an improved particle swarm optimization (IPSO) algorithm to obtain the GNSS integer ambiguity with the double differenced (DD) float resolution and its corresponding covariance matrix. First, we introduced population maturity to the standard PSO (SPSO) algorithm for the adaptive adjustment of inertia weight. Next, to improve the global convergence and robustness of the SPSO algorithm, we adopted population classification and constructed a Gauss mutation for the particle evolution process of the optimal population. Then, we applied the IPSO algorithm in the field of GNSS AR, called IPSO–AR. Finally, we evaluated the performance of the IPSO–AR algorithm under different DD ambiguity float resolutions with various dimensions and precisions. Numerical results showed that compared with the SPSO–AR algorithm, the IPSO–AR algorithm has a superior correct rate, but low efficiency. Under the appropriate parameter settings, the efficiency of the IPSO–AR algorithm is mainly dependent on the dimensions of DD ambiguity, whereas the correct rate of the IPSO–AR algorithm is mainly dependent on the precision of DD ambiguity. The proposed IPSO–AR algorithm has potential applications under the conditions of few visible satellites or constrained baseline length.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: GNSS positioning and interference · Inertial Sensor and Navigation · Geophysics and Gravity Measurements
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Geology Engineering and Geomantic, Chang’an University, Xi’an 710054, China
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Funding
the Fundamental Research Funds for the Central Universities, Chang’an University · the Programs of the National Natural Science Foundation of China
References (40)
Show source-provided references
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