摘要
时钟同步技术是基于倒GPS(IGPS)基站网络来进行目标定位的重要研究内容。提出了一种与IGPS基站时钟结合的自适应离散卡尔曼滤波方法,该方法利用测量新息和状态修正序列在估计窗内分段静止的特性,克服了传统卡尔曼滤波过程过分依赖于数学模型和统计模型正确性的问题。通过这种方法可以在线实时修正和转换IGPS基站间的时钟相位偏差和时钟偏移,找出最佳时钟适应曲线,并估计过程噪声和测量噪声的协方差矩阵。仿真结果表明,该方法能够提高IGPS基站间的时钟同步精度,使同步精度达到微秒量级。
Clock synchronization technology is an important research content based on IGPS base-station networks of target positioning. An adaptive discrete-time Kalman filtering method combined with IGPS basestation clocks is proposed. The algorithm is carried out by using the property that the measurement innovation sequence is piecewise stationary inside an estimation window. The algorithm also overcomes the traditional Kalman filtering process which excessively relies on the correctness of the mathematical and stastical models. Using this algorithm, the relative phase offsets and clock skews among the clocks of IGPS base-stations can be corrected and converted. Also, the best fit line over the observations on line can be found, and the covariance matrices of the process and measurement noises are estimated. Simulation results show that the proposed algorithm can improve the accuracy of clock synchronization among IGPS base-stations and the synchronization accuracy can reach the microsecond order of magnitude.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2009年第7期1710-1714,共5页
Systems Engineering and Electronics
基金
北京市教育委员会共建基金资助课题(100070522)
关键词
倒GPS时钟同步
自适应算法
卡尔曼滤波
状态估计
inverse GPS
clock synchronization
adaptive algorithm
Kalman filtering
state estimation
