New aircraft terrain matching algorithm based on particle swarm optimization

He Yanping; Liu Xinxue; Cai Yanping; Li Yaxiong; Zhu Yu

doi:10.3788/IRLA201645.S114002

In order to improve the positioning accuracy of traditional terrain matching algorithm, a new aircraft terrain matching algorithm based on particle swarm optimization was put forward. The search scope of true location was programmed by taking the measured position of referenced navigation system as the center, terrain elevation data was extracted from the referenced topographic map, then the particle swarm optimization algorithm was introduced into the matching area for searching, and the parameter of pixel height of the terrain profile was used as the particle in particle swarm. On this basis of above, correlation function of normalized product was applied as fitness function of particle, then the degree of similarity of the referenced map with profile of real-time image was compared by maximum fitness value, finally through the simulation analysis, comparison of matching accuracy and time based on TERCOM algorithm and PSO algorithm was presented. Simulation results show that the effect of matching based on PSO algorithm is better than traditional TERCOM algorithm, and matching time is slightly longer than TERCOM, but meet the real-time requirement.

New aircraft terrain matching algorithm based on particle swarm optimization

1. Rockets Army Engineering University,Xi'an 710025,China

Received Date: 2016-01-10

Rev Recd Date: 2016-02-08

Publish Date: 2016-05-25

Key words:

Abstract: In order to improve the positioning accuracy of traditional terrain matching algorithm, a new aircraft terrain matching algorithm based on particle swarm optimization was put forward. The search scope of true location was programmed by taking the measured position of referenced navigation system as the center, terrain elevation data was extracted from the referenced topographic map, then the particle swarm optimization algorithm was introduced into the matching area for searching, and the parameter of pixel height of the terrain profile was used as the particle in particle swarm. On this basis of above, correlation function of normalized product was applied as fitness function of particle, then the degree of similarity of the referenced map with profile of real-time image was compared by maximum fitness value, finally through the simulation analysis, comparison of matching accuracy and time based on TERCOM algorithm and PSO algorithm was presented. Simulation results show that the effect of matching based on PSO algorithm is better than traditional TERCOM algorithm, and matching time is slightly longer than TERCOM, but meet the real-time requirement.

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Reference (10)

[1]	Wu Kang, Zhao Long. Alogorithm research on navigation matching apply to airlines[J]. Piezoelectrics Acoustooptics, 2010, 32(5):754-761. (in Chinese) 吴康, 赵龙. 适用航空的导航匹配算法研究[J]. 压电与声光, 2010, 32(5):754-761.
[2]	Li Xiongwei, Liu Jianye, Kang Guohua. Development and application of TERCOM elevation-aided navigation system[J]. Journal of Chinese Inertial Technology, 2006, 14(1):34-40. (in Chinese) 李雄伟, 刘建业, 康国华. TERCOM地形高程辅助导航系统发展及应用研究[J]. 中国惯性技术学报, 2006, 14(1):34-40.
[3]	Liu Hong, Gao Yongqi, Shen Jian. Under water terrain matching techniques based on combination of PMF and TERCOM algorithms[J]. Torpedo Technology, 2012, 20(6):437-442. (in Chinese) 刘洪, 高永琪, 谌剑. 基于PMF和TERCOM组合算法的水下地形匹配技术[J]. 鱼雷技术, 2012, 20(6):437-442.
[4]	Yan Li, Cui Chenfeng, Wu Hualin. A gravity matching algorithm based on TERCOM[J]. Geomatics and Information Science of Wuhan University, 2009, 34(3):261-264. (in Chinese) 闫利, 崔晨风, 吴华玲. 基于TERCOM算法的重力匹配[J]. 武汉大学学报(信息科学版), 2009, 34(3):261-264.
[5]	Zhao Jianhu, Wang Shengping, Wang Aixue. An improved TERCOM algorithm for underwater geomagnetic matching navigation[J]. Science of Wuhan University, 2009, 34(11):1320-1322.
[6]	Wang Shengping, Zhang Hongmei, Zhao Jianhu, et al. Marine geomagnetic navigation technology based on integration of TERCOM and ICCP[J]. Geomatics and Information Science of Wuhan University, 2011, 36(10):1209-1212. (in Chinese) 王胜平, 张红梅, 赵建虎, 等. 利用TERCOM与ICCP进行联合地磁匹配导航[J]. 武汉大学学报(信息科学版), 2011, 36(10):1209-1212.
[7]	Lv Wentao, Wang Honglun, Liu Chang, et al. Design and simulation of terrain matching aided navigation system for UAVs[J]. Electronics Optics Control, 2014, 21(5):63- 67. (in Chinese) 吕文涛, 王宏伦, 刘畅, 等. 无人机地形匹配辅助导航系统设计与仿真[J]. 电光与控制, 2014, 21(5):63- 67.
[8]	Zhang Tao, Xu Xiaosu, Li Peijuan. Underwater terrain matching algorithmbased on chaotic optimization[J]. Journal of Chinese Inertial Technology, 2009, 17(2):156-164. (in Chinese) 张涛, 徐晓苏, 李佩娟. 混沌优化水下地形匹配算法研究[J]. 中国惯性技术学报, 2009, 17(2):156-164.
[9]	Xu Zunyi, Wei Dong, Li Jing, et al. Simulation research on the correlation matching algorithm based on particle swarm optimization for aircraft geomagnetic aid navigation[J]. Ship Science and Technology, 2011, 33(11):3-6. (in Chinese) 徐遵义, 魏东, 李璟, 等. 基于粒子群优化的飞行器地磁相关匹配新算法仿真[J]. 舰船科学技术, 2011, 33(11):3-6.
[10]	Zhang Kai, Zhao Jianhu, Wang Qie. Study on recognition and classification of appropiate matching area for under water navigation based on SVM[J]. Journal of Geodesy and Geodynamics, 2013, 33(6):72-77. (in Chinese) 张凯, 赵建虎, 王锲. 基于支持向量机的水下地形匹配导航中适配区划分方法研究[J]. 大地测量与地球动力学, 2013, 33(6):72-77.

New aircraft terrain matching algorithm based on particle swarm optimization

doi: 10.3788/IRLA201645.S114002

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