环路跟踪卡尔曼滤波算法的性能分析

基于卡尔曼滤波的环路跟踪算法多是通过一定仿真证明算法性能,没有系统性性能评估,难以较好指导工程应用。在原有算法基础上进行了优化,并系统性地对比分析、评估了基于卡尔曼环路滤波算法性能,以期为算法工程化提供指导。首先提出对跟踪环路反馈调整量进行预测,使之更符合系统实际,减小环路跟踪误差。而后基于卫星信号模拟器输出信号和自生产信号源,充分评估基于卡尔曼滤波环路跟踪算法的收敛时间和灵敏度。仿真结果表明,相比目前工程常用的二阶FFL辅助三阶PLL算法,基于卡尔曼滤波环路跟踪算法能够缩短环路所需稳定时间约90%,并能提升跟踪灵敏度约5 d B,有效改善弱信号场景中接收机输出信息的完好性和连续性。

Performance analysis of tracking loop Kalman filter algorithm

Some simulations have been done to prove the advantages of the tracking loop algorithm based on Kalman filter,but there is few systematic performance evaluation.These results have little guide to the engineering application.In this paper,the original algorithm is optimized,and the performance of the tracking loop based on Kalman filtering is systematically-comparatively analyzed and evaluated.First of all,the tracking loop feedback adjustment is proposed to make it more in line with the actual system situation.Then based on the signal from the satellite signal simulator and the signal source from the production,the sensitivity and convergence time of the tracking loop algorithm based on Kalman filter is fully evaluated.The simulation results show that,compared with the current two-order FFL aided three-order PLL algorithm,the tracking loop algorithm based on Kalman filter reduces the convergence time by about 90％,and improves the tracking sensitivity by about 5dB,which effectively improves the integrity and continuity of the receiver output information in weak signal scene.