Fast Two-dimensional Positioning Method of Crab Pulsar Based on Multiple Optimization Algorithms

Abstract In the two-dimensional positioning method of pulsars, the grid method is used to provide non-sensitive direction and positional estimates. However, the grid method has a high computational load and low accuracy due to the interval of the grid. To improve estimation accuracy and reduce the computational load, we propose a fast two-dimensional positioning method for the crab pulsar based on multiple optimization algorithms (FTPCO). The FTPCO uses the Levenberg–Marquardt (LM) algorithm, three-point orientation (TPO) method, particle swarm optimization (PSO) and Newton–Raphson-based optimizer (NRBO) to substitute the grid method. First, to avoid the influence of the non-sensitive direction on positioning, we take an orbital error and the distortion of the pulsar profile as optimization objectives and combine the grid method with the LM algorithm or PSO to search for the non-sensitive direction. Then, on the sensitive plane perpendicular to the non-sensitive direction, the TPO method is proposed to fast search the sensitive direction and sub-sensitive direction. Finally, the NRBO is employed on the sensitive and sub-sensitive directions to achieve two-dimensional positioning of the Crab pulsar. The simulation results show that the computational load of the FTPCO is reduced by 89.4% and the positioning accuracy of the FTPCO is improved by approximately 38% compared with the grid method. The FTPCO has the advantage of high real-time accuracy and does not fall into the local optimum.

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Publication Details

Journal
Research in Astronomy and Astrophysics
Published
2024-09-03
DOI
https://doi.org/10.1088/1674-4527/ad76ec
Citations
2
Primary Topic
Inertial Sensor and Navigation
Type
article
Field-Weighted Citation Impact
2.60
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article

Fast Two-dimensional Positioning Method of Crab Pulsar Based on Multiple Optimization Algorithms

Xiaolin Ning, Xin Ma, J. Chen, Jin Liu
2 citations
Research in Astronomy and Astrophysics
Inertial Sensor and Navigation
2.60
article

Fast Two-dimensional Positioning Method of Crab Pulsar Based on Multiple Optimization Algorithms

Xiaolin Ning, Xin Ma, J. Chen, Jin Liu
article en
2 citations

Abstract

Abstract In the two-dimensional positioning method of pulsars, the grid method is used to provide non-sensitive direction and positional estimates. However, the grid method has a high computational load and low accuracy due to the interval of the grid. To improve estimation accuracy and reduce the computational load, we propose a fast two-dimensional positioning method for the crab pulsar based on multiple optimization algorithms (FTPCO). The FTPCO uses the Levenberg–Marquardt (LM) algorithm, three-point orientation (TPO) method, particle swarm optimization (PSO) and Newton–Raphson-based optimizer (NRBO) to substitute the grid method. First, to avoid the influence of the non-sensitive direction on positioning, we take an orbital error and the distortion of the pulsar profile as optimization objectives and combine the grid method with the LM algorithm or PSO to search for the non-sensitive direction. Then, on the sensitive plane perpendicular to the non-sensitive direction, the TPO method is proposed to fast search the sensitive direction and sub-sensitive direction. Finally, the NRBO is employed on the sensitive and sub-sensitive directions to achieve two-dimensional positioning of the Crab pulsar. The simulation results show that the computational load of the FTPCO is reduced by 89.4% and the positioning accuracy of the FTPCO is improved by approximately 38% compared with the grid method. The FTPCO has the advantage of high real-time accuracy and does not fall into the local optimum.

Research in Astronomy and AstrophysicsVol. 24(10)
Hefei University (CN), Wuhan University of Science and Technology (CN), Beihang University (CN)
Openalex Percentile: Top 8%
Inertial Sensor and Navigation
2.60
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