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Improved Adaptive Particle Filter for Integrated Navigation System

Mengchu Tian1, Yuming Bo1, Zhimin Chen2,3, Panlong Wu1, Gaopeng Zhao1

School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China
China Satellite Maritime Tracking and Controlling Department, Jiangyin, 214431, China)
Corresponding author.

Computer Modeling in Engineering & Sciences 2015, 108(5), 285-301.


Particle filter based on particle swarm optimization algorithm is not precise enough and easily trapping in local optimum, it is difficult to satisfy the requirement of advanced integrated navigation system. To solve these problems, an improved adaptive particle filter based on chaos particle swarm was proposed and used in GPS/INS integrated navigation system. This algorithm introduced chaos sequence to update the weight and threshold, which could improve the quality of samples and reduce the local optimization and enhance the global searching ability. In addition, the avoid factor was set which made the particles be away from low likelihood area. Finally, simulation results indicate that this algorithm improved the accuracy and robustness of GPS/INS integrated navigation system.


Cite This Article

APA Style
Tian, M., Bo, Y., Chen, Z., Wu, P., Zhao, G. (2015). Improved adaptive particle filter for integrated navigation system. Computer Modeling in Engineering & Sciences, 108(5), 285-301.
Vancouver Style
Tian M, Bo Y, Chen Z, Wu P, Zhao G. Improved adaptive particle filter for integrated navigation system. Comput Model Eng Sci. 2015;108(5):285-301
IEEE Style
M. Tian, Y. Bo, Z. Chen, P. Wu, and G. Zhao "Improved Adaptive Particle Filter for Integrated Navigation System," Comput. Model. Eng. Sci., vol. 108, no. 5, pp. 285-301. 2015.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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