摘要
在伪卫星自主组网定位的时钟同步问题中,卡尔曼滤波(Kalman Filter,KF)算法因迭代时间短而被广泛应用,但是其精度不高。相反地,粒子滤波(Particle Filter,PF)算法精度高,但是其迭代时间长。在此基础上,提出一种混合优化算法(Hybrid Optimizing Algorithm,HOA),该算法将卡尔曼滤波算法和粒子滤波算法有机结合,兼具卡尔曼滤波算法迭代时间短和粒子滤波算法精度高的优点。仿真结果表明,HOA算法具有更短的迭代时间,并且能够显著提高时钟同步精度。
In the clock synchronization of pseudo-satellite autonomous network positioning,the Kalman Filter(KF)algorithm is widely used because of its short iteration time,but its accuracy is not high.In contrast,the particle filter(PF)algorithm has high precision,but its iteration time is long.On this basis,a hybrid optimizing algorithm(HOA)is proposed,which combines the Kalman filter algorithm and the particle filter algorithm.HOA not only inherits the short iteration time of the Kalman filter algorithm,but also has the advantage of high precision of particle filter algorithm.The simulation results show that the HOA algorithm has a shorter iteration time and can significantly improve clock synchronization accuracy.
作者
黄星
赵利
蔡成林
唐俏笑
陈振林
HUANG Xing;ZHAO Li;CAI Cheng-lin;TANG Qiao-xiao;CHEN Zhen-lin(School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China)
出处
《测控技术》
2021年第1期95-99,共5页
Measurement & Control Technology
基金
国家自然科学基金项目(61771150)
桂林电子科技大学创新项目(2018YJCX27)。
关键词
时钟同步
伪卫星
卡尔曼滤波
粒子滤波
混合优化算法
clock synchronization
pseudo-satellite
Kalman Filter
particle filter
hybrid optimizing algorithm