卫星导航弱信号的变维卡尔曼滤波跟踪算法  

Weak GNSS signal tracking algorithm based on variable dimension Kalman filter

作　　者：余小游[1] 高亭亭[1] 孙广富[2] 唐小妹[2] 倪少杰[2] 

机构地区：[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

出　　处：《国防科技大学学报》2015年第3期56-60,共5页Journal of National University of Defense Technology

基　　金：国家自然科学基金资助项目(41304026)

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30d BHz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%。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. 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.

关 键 词：变维卡尔曼滤波 载波跟踪 动态切换 自适应跟踪 

分 类 号：TN927[电子电信—通信与信息系统]