Suppressing jitter noises in a phase locked loop（ PLL） is of great importance in order to keep precise and continuous track of global positioning system （GPS）signals characterized by low carrier-to-noise ratio（ C...Suppressing jitter noises in a phase locked loop（ PLL） is of great importance in order to keep precise and continuous track of global positioning system （GPS）signals characterized by low carrier-to-noise ratio（ C/No ）. This article proposes and analyzes an improved Kalman-filter-based PLL to process weak carrier signals in GPS software receivers. After reviewing the optimal-bandwidth-based traditional second-order PLL, a Kalman-filter-based estimation algorithm is implemented for the new PLL by decorrelating the model error noises and the measurement noises. Finally,the efficiency of this new Kalman-filter-based PLL is verified by experimental data. Compared to the traditional second-order PLL, this new PLL is in position to make correct estimation of the carrier phase differences and Doppler shifts with less overshoots and noise disturbances and keeps an effective check on the disturbances out of jitter noises in PLL. The results show that during processing normal signals,this improved PLL reduces the standard deviation from 0. 010 69 cycle to 0. 007 63 cycle, and for weak signal processing,the phase jitter range and the Doppler shifts can be controlled within ± 17° and ±5 Hz as against ±25° and ＋ 15 Hz by the traditional PLL.展开更多
对光纤陀螺随机噪声的ARMA建模及卡尔曼滤波方法进行了研究。针对ARMA(Auto-Regressive and Moving Average自回归滑动平均)模型的有色噪声在状态方程中不能通过传统的状态扩充法进行白化的问题,提出了新的噪声白化方法:采用增广最小二...对光纤陀螺随机噪声的ARMA建模及卡尔曼滤波方法进行了研究。针对ARMA(Auto-Regressive and Moving Average自回归滑动平均)模型的有色噪声在状态方程中不能通过传统的状态扩充法进行白化的问题,提出了新的噪声白化方法:采用增广最小二乘法估计ARMA模型的参数,同时提取出ARMA模型中的驱动白噪声,从而可以把ARMA模型中的有色噪声项作为控制项放入系统的状态方程,通过Sage-Husa的次优无偏MAP(Maximum A Posteriori,极大后验)噪声统计估值器对系统噪声的统计特性进行估计,实现了系统噪声的白化。在此基础上应用自适应卡尔曼滤波,有效消除了误差,得到状态值的准确估计。实验结果表明,对于随机噪声的自相关和互相关特性均呈现拖尾性质的光纤陀螺,采用新方法比传统基于AR模型的Kalman滤波降噪方法滤除噪声的效果提高了10%以上。展开更多
基金National Natural Science Foundation of China(40671155)National High-tech Research and Development Programof China(2006AA12A108)Research Program of Hong Kong Polytech-nic University(G-U203)
文摘Suppressing jitter noises in a phase locked loop（ PLL） is of great importance in order to keep precise and continuous track of global positioning system （GPS）signals characterized by low carrier-to-noise ratio（ C/No ）. This article proposes and analyzes an improved Kalman-filter-based PLL to process weak carrier signals in GPS software receivers. After reviewing the optimal-bandwidth-based traditional second-order PLL, a Kalman-filter-based estimation algorithm is implemented for the new PLL by decorrelating the model error noises and the measurement noises. Finally,the efficiency of this new Kalman-filter-based PLL is verified by experimental data. Compared to the traditional second-order PLL, this new PLL is in position to make correct estimation of the carrier phase differences and Doppler shifts with less overshoots and noise disturbances and keeps an effective check on the disturbances out of jitter noises in PLL. The results show that during processing normal signals,this improved PLL reduces the standard deviation from 0. 010 69 cycle to 0. 007 63 cycle, and for weak signal processing,the phase jitter range and the Doppler shifts can be controlled within ± 17° and ±5 Hz as against ±25° and ＋ 15 Hz by the traditional PLL.
文摘对光纤陀螺随机噪声的ARMA建模及卡尔曼滤波方法进行了研究。针对ARMA(Auto-Regressive and Moving Average自回归滑动平均)模型的有色噪声在状态方程中不能通过传统的状态扩充法进行白化的问题,提出了新的噪声白化方法:采用增广最小二乘法估计ARMA模型的参数,同时提取出ARMA模型中的驱动白噪声,从而可以把ARMA模型中的有色噪声项作为控制项放入系统的状态方程,通过Sage-Husa的次优无偏MAP(Maximum A Posteriori,极大后验)噪声统计估值器对系统噪声的统计特性进行估计,实现了系统噪声的白化。在此基础上应用自适应卡尔曼滤波,有效消除了误差,得到状态值的准确估计。实验结果表明,对于随机噪声的自相关和互相关特性均呈现拖尾性质的光纤陀螺,采用新方法比传统基于AR模型的Kalman滤波降噪方法滤除噪声的效果提高了10%以上。
