| 引用本文: | 余小游,高亭亭,孙广富,等.卫星导航弱信号的变维卡尔曼滤波跟踪算法.[J].国防科技大学学报,2015,37(3):56-60.[点击复制] |
| YU Xiaoyou,GAO Tingting,SUN Guangfu,et al.Weak GNSS signal tracking algorithm based on variable dimension Kalman filter[J].Journal of National University of Defense Technology,2015,37(3):56-60[点击复制] |
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| 卫星导航弱信号的变维卡尔曼滤波跟踪算法 |
| 余小游1, 高亭亭1, 孙广富2, 唐小妹2, 倪少杰2 |
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(1.湖南大学 信息科学与工程学院，湖南 长沙 410082;2.国防科技大学 电子科学与工程学院，湖南 长沙 410073)
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| 摘要: |
| 复杂环境下的多普勒频移变化及信号功率衰减均会造成载波跟踪偏差较大甚至失锁，针对标准卡尔曼滤波算法跟踪机动目标时不能同时满足高动态及高灵敏度要求的问题，提出一种基于变维卡尔曼滤波的载波跟踪算法。引入机动和非机动两种载波跟踪模型，通过机动检测因子监视载波动态变化，实时高效地切换载波跟踪模型，从而实现对载波机动和非机动状态的自适应跟踪，抑制机动改变引起的较大误差突跳。理论分析和仿真结果表明，该算法在低至30dBHz弱信号环境下，相比基于标准卡尔曼滤波的跟踪算法，其在目标动态突变时相位跟踪误差减小约37.5%，频率跟踪误差减小约77%。 |
| 关键词: 变维卡尔曼滤波 载波跟踪 动态切换 自适应跟踪 |
| DOI：10.11887/j.cn.201503010 |
| 投稿日期：2015-03-07 |
| 基金项目:国家自然科学基金资助项目（41304026） |
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| Weak GNSS signal tracking algorithm based on variable dimension Kalman filter |
| YU Xiaoyou1, GAO Tingting1, SUN Guangfu2, TANG Xiaomei2, NI Shaojie2 |
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(1. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China;2. College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China)
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| Abstract: |
| Doppler shift and signal power attenuation in the complex environment both can make deviation bigger or even lose lock. Because the conventional Kalman filter can’t meet the dual requirements of high dynamic and high sensitivity when tracking maneuvering targets, a new carrier tracking method based on variable dimension Kalman filter was presented. By introducing motor model and non-monitor model of the carrier tracking and through putting in a maneuvering detector to monitor target movements, the real-time and effective switching of carrier tracking model was realized, so the adaptive tracking of carrier in motor and non-monitor state was achieved and the error caused by the change of maneuverability was overcome. 〖JP3〗Theoretical analysis and simulation results show that: comparing with the tracking algorithm based on standard Kalman filter, the phase tracking error of this algorithm is reduced by about 37.5% and the frequency tracking error is reduced by about 77% in weak carrier to noise ratio as low as 30dBHz environment. |
| Keywords: variable dimension Kalman filter carrier tracking dynamic switching adaptive tracking |
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