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粒子群优化粒子滤波的接收机自主完好性监测

王尔申 曲萍萍 庞涛 蓝晓宇 陈佳美

王尔申, 曲萍萍, 庞涛, 等 . 粒子群优化粒子滤波的接收机自主完好性监测[J]. 北京航空航天大学学报, 2016, 42(12): 2572-2578. doi: 10.13700/j.bh.1001-5965.2016.0362
引用本文: 王尔申, 曲萍萍, 庞涛, 等 . 粒子群优化粒子滤波的接收机自主完好性监测[J]. 北京航空航天大学学报, 2016, 42(12): 2572-2578. doi: 10.13700/j.bh.1001-5965.2016.0362
WANG Ershen, QU Pingping, PANG Tao, et al. Receiver autonomous integrity monitoring based on particle swarm optimization particle filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(12): 2572-2578. doi: 10.13700/j.bh.1001-5965.2016.0362(in Chinese)
Citation: WANG Ershen, QU Pingping, PANG Tao, et al. Receiver autonomous integrity monitoring based on particle swarm optimization particle filter[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(12): 2572-2578. doi: 10.13700/j.bh.1001-5965.2016.0362(in Chinese)

粒子群优化粒子滤波的接收机自主完好性监测

doi: 10.13700/j.bh.1001-5965.2016.0362
基金项目: 

国家自然科学基金 61571309

国家自然科学基金 61101161

辽宁省“百千万人才工程” 

详细信息
    通讯作者:

    王尔申, 男, 博士, 副教授。主要研究方向:卫星导航、航空电子。Tel.:024-89723755, E-mail:wanges_2016@126.com

  • 中图分类号: V241.6;TN967.1

Receiver autonomous integrity monitoring based on particle swarm optimization particle filter

Funds: 

National Natural Science Foundation of China 61571309

National Natural Science Foundation of China 61101161

Liaoning BaiQianWan Talents Program 

More Information
  • 摘要:

    接收机自主完好性监测(RAIM)是航空卫星导航接收机必不可少的功能,为保持全球卫星导航系统(GNSS)在卫星发生故障时系统性能不降级,需要对卫星故障进行检测和隔离。针对接收机观测噪声非高斯分布的特点,提出一种基于粒子群优化粒子滤波(PSO-PF)的故障检测和隔离算法。通过粒子群优化粒子滤波对状态估计进行一致性检验实现故障检测。采集实测数据验证算法的检测性能,并与基于基本粒子滤波的完好性监测算法进行比较,结果表明:本文所提算法在非高斯测量噪声下可检测并隔离全球定位系统(GPS)故障卫星,其性能优于基于基本粒子滤波的完好性监测算法性能,对研究北斗卫星导航系统(BDS)接收机自主完好性监测具有一定的意义。

     

  • 图 1  PSO-PF RAIM原理框图

    Figure 1.  Principle block diagram of RAIM based on PSO-PF

    图 2  偏差为15 m时累加LLR值和故障检测判决函数比较

    Figure 2.  Cumulative LLR and comparison of decision function for fault detection under 15 m step failure

    图 3  偏差为20 m时累加LLR值和故障检测判决函数比较

    Figure 3.  Cumulative LLR and comparison of decision function for fault detection under 20 m step failure

    图 4  偏差为30 m时累加LLR值和故障检测判决函数比较

    Figure 4.  Cumulative LLR and comparison of decision function for fault detection under 30 m step failure

    表  1  PSO-PF RAIM算法和PF RAIM算法的故障检测告警时刻比较

    Table  1.   Comparison of alarm time for fault detection for PSO-PF RAIM algorithm and PF RAIM algorithm

    伪距偏差/m 告警时刻/s
    PSO-PF RAIM算法 PF RAIM算法
    15 510 518
    20 505 514
    30 505 509
    下载: 导出CSV

    表  2  不同偏差下PSO-PF RAIM算法和PF RAIM算法的平均有效粒子数(N=50)

    Table  2.   Average effective number of particles under different bias for PSO-PF RAIM algorithm and PF RAIM algorithm (N=50)

    伪距偏差/m 平均有效粒子数
    PSO-PF RAIM算法 PF RAIM算法
    15 43.8 42.1
    20 44.7 42.0
    30 44.6 42.8
    下载: 导出CSV
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出版历程
  • 收稿日期:  2016-05-03
  • 录用日期:  2016-07-22
  • 网络出版日期:  2017-12-20

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