Performance Analysis of Adaptive Kalman Filter for BeiDou Signal Tracking in High Dynamics
conventional receivers,scalar tracking loops are used and all visible satellites are tracked by individual channels and no information is shared with other channels.Although each tracking channel can independently work best but the navigation performance decreases badly in degraded signal environments.On the other hand,vector based tracking architectures take advantage of inter-channel information sharing and use this information to estimate receiver’s position and this navigation information is used by tracking loops to predict code phase and carrier frequencies.In vector tracking receivers,both tracking and navigation tasks are performed by single navigation filter,mostly extended kalman filter.Still vector tracking receivers are vulnerable under high dynamics.The precision of kalman filter is highly relies on process and measurement noise covariance.In case of poorly designed noise parameters,filter can diverge.In this paper,we proposed and studied an algorithm to update measurement and process noise covariance matrices adaptively with changing dynamics.Performance results showed that proposed algorithm works better than conventional extended kalman filter in degraded signal environments.
Scalar tracking Vector tracking High dynamics Extended kalman filter Adaptive kalman filter
Muhammad Adeel XinChen Peilin Liu
Shanghai Key Lab of BeiDou Navigation and Location-Based Service,Electron.Info.& Electric. Eng. School,Shanghai Jiao Tong University,Shanghai,China,200240
国内会议
西安
英文
1-13
2015-05-13（万方平台首次上网日期，不代表论文的发表时间）