基于自适应EKF的高动态载波跟踪算法

High Dynamic Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filtering

针对载波跟踪算法在大频偏或动态剧烈变化时易失锁的问题,提出一种无数据辅助情况下基于自适应R/Q扩展卡尔曼滤波(AEKF)的高动态载波跟踪算法。该算法在AEKF代替鉴相器和滤波器的环路结构基础上,引入两倍相位转换来消除数据位跳变的影响,并利用载噪比估计方法和基于加加速度的信号动态监测方法来修正观测噪声协方差(R)和系统状态噪声方差(Q),进而兼顾环路的跟踪精度和动态稳定性。实验结果表明:利用该算法的GPS软件接收机能够在加速度200 g,瞬间加加速度10 000 g/s的动态指标下正常工作。

For carrier tracking algorithm,it is easy to lose lock under high dynamic situation,which has large Doppler frequency shift or dynamic change dramatically. To solve the problem,this paper presents a non-data-aided high dynamic carrier tracking algorithm Based on adaptive extended kalman filtering （AEKF） with measurement and process noise covariance. Firstly,the algorithm substitute AEKF for discriminator and filter ,and eliminate the influence of data bit jump,with double phase transformation processing. Secondly,it adopts the signal-to-noise ratio estimator and the monitoring method of signal dynamic with jerk to Estimating and calibrating the statistical characteristics of noise, which is helpful to achieve a better balance between the dynamic stability and tracking accuracy. By using the algorithm of GPS software receiver ,The results show that the algorithm could works normally with the dynamic indexes of acceleration on up to 200 g and instantaneous jerk up to 10 000 g/s.