北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (2): 259-265.doi: 10.13700/j.bh.1001-5965.2018.0281

• 论文 • 上一篇    下一篇

基于混沌粒子群优化的北斗/GPS组合导航选星算法

王尔申1,2,3, 贾超颖1, 曲萍萍1, 黄煜峰1, 庞涛1, 别玉霞1, 姜毅4   

  1. 1. 沈阳航空航天大学 电子信息工程学院, 沈阳 110136;
    2. 北京航空航天大学 电子信息工程学院, 北京 10008;
    3. 沈阳航空航天大学 辽宁省通用航空重点实验室, 沈阳 110136;
    4. 大连海事大学 水上智能交通行业重点实验室, 大连 116026
  • 收稿日期:2018-05-17 出版日期:2019-02-20 发布日期:2019-03-04
  • 通讯作者: 王尔申 E-mail:wanges_2016@126.com
  • 作者简介:王尔申男,博士,教授,硕士生导师。主要研究方向:卫星导航定位技术、接收机信号处理算法、航空电子技术。贾超颖女,硕士研究生。主要研究方向:卫星导航定位技术。
  • 基金资助:
    国家自然科学基金(61571309,61101161);中央高校基本科研业务费专项资金(3132016317);辽宁“百千万人才工程”;辽宁省教育厅项目(L2014059,L201716,UPRP2018198);辽宁省高等学校优秀人才支持计划(LR2016069)

BDS/GPS integrated navigation satellite selection algorithm based on chaos particle swarm optimization

WANG Ershen1,2,3, JIA Chaoying1, QU Pingping1, HUANG Yufeng1, PANG Tao1, BIE Yuxia1, JIANG Yi4   

  1. 1. School of Electronic and Information Engineering, Shenyang Aerospace University, Shenyang 110136, China;
    2. School of Electronic and Information Engineering, Beihang University, Beijing 10008;
    3. Liaoning General Aviation Key Laboratory, Shenyang Aerospace University, Shenyang 110136, China;
    4. Key Laboratory of Intelligent Waterway Transport of Ministry of Transport, Dalian Maritime University, Dalian 116026, China
  • Received:2018-05-17 Online:2019-02-20 Published:2019-03-04
  • Supported by:
    National Natural Science Foundation of China (61571309,61101161); the Fundamental Research Funds for the Central Universities (3132016317); Liaoning BaiQianWan Talents Program; Scientific Study Project for Liaoning Province Ministry of Education (L2014059,L201716,UPRP2018198); Program for Liaoning Excellent Talents in University (LR2016069)

摘要: 全球卫星导航系统(GNSS)接收机在接收信号的过程中会受到诸如建筑物遮挡、信号干扰等因素的影响,无法得到全部可见星。为减轻多星座组合接收机的处理负担,研究利用部分可见卫星进行定位的快速选星算法,提出了一种基于混沌粒子群优化(CPSO)的北斗/GPS组合导航选星算法。首先,对当前历元时刻可见卫星进行连续编码,按照选星数目分组,每个分组视为一个粒子。然后,通过混沌映射初始化粒子种群,选取几何精度因子(GDOP)作为评价粒子优劣的适应度函数;粒子通过粒子群优化算法的速度-位移模型更新自身位置,逐渐趋近空间卫星几何分布较好的卫星组合全局最优解。最后,采集北斗/GPS实际数据对选星算法进行仿真验证和性能比较,结果表明,所提算法在选星颗数多于5颗时,单次选星耗时为遍历法选星的37.5%,选星结果的几何精度因子计算误差在0~0.6之间。该算法可适用于北斗/GPS组合导航定位不同选星颗数的情况。

关键词: 北斗/GPS组合导航, 选星, 混沌粒子群优化(CPSO), 几何精度因子(GDOP), 适应度函数

Abstract: In the process of signal receiving, global navigation satellite system (GNSS) receiver will be affected by factors such as building blockages and signal interference and will not be able to obtain all the visible satellites; moreover, in order to reduce the processing burden of multi-constellation receivers, the fast satellite selection algorithm using partial visible satellites to achieve positioning solution is investigated, and the BDS/GPS integrated navigation satellite selection algorithm based on chaos particle swarm optimization (CPSO) is proposed. First, the visible satellites are continuously numbered and randomly divided into groups. Each group is regarded as a particle. Then, chaotic maps are used to select several groups from all grouping spaces to form initial population. The geometric dilution of precision (GDOP) is chosen as fitness function to evaluate the particle's quality. In addition, the particle's position is updated by the velocity-displacement model of the PSO algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. Finally, using real navigation data, the algorithm is verified by simulation experiments. The results demonstrate that when the number of selected satellite is more than 5, the time that the proposed algorithm takes to select satellite once is 37.5% of the time that the traversing algorithm takes, and the GDOP error of the selected satellites is between 0 and 0.6. Moreover, the proposed algorithm can be applied to the case of different numbers of selected satellite in BDS/GPS integrated navigation.

Key words: BDS/GPS integrated navigation, satellite selection, chaos particle swarm optimization (CPSO), geometric dilution of precision (GDOP), fitness function

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