GNSS/INS组合导航的随机时延卡尔曼滤波  

Random Delay Kalman Filtering of GNSS/INS Integrated Navigation

作　　者：潘新宇 赵英策 李建勋[1] PAN Xin-yu;ZHAO Ying-ce;LI Jian-xun(Department of Automation, Shanghai Jiaotong University, Shanghai 200240;Shenyang Aircraft Design and Research Institute of AVIC, Shenyang 110035, China)

机构地区：[1]上海交通大学自动化系,上海200240 [2]中国航空工业沈阳飞机设计研究所,辽宁沈阳110035

出　　处：《指挥控制与仿真》2022年第1期26-31,共6页Command Control & Simulation

基　　金：国家自然科学基金(61673265);国家重点研究开发项目(MJ-2017-S-38)。

摘　　要：组合导航系统在实际应用中存在信号传输和解算的延时影响,直接使用带有延迟的测量数据会导致滤波算法的精度下降甚至发散。针对这类测量具有随机时延的滤波问题,提出了随机时延卡尔曼滤波算法,该算法的核心是将新的量测用于更新过去的多个状态,以此来对时延进行补偿。GNSS与INS的组合导航系统仿真结果表明,所设计的滤波算法在面对量测具有随机延时的情况下,可以减轻滤波后的尖峰现象,降低估计结果的误差。In practical applications,the integrated navigation system has the influence of delay in signal transmission and calculation.Directly using the measurement data with delay will cause the accuracy of the filtering algorithm to decrease or even diverge.In order to solve the filtering problem of this kind of measurement with random delay,this paper proposes the random delay Kalman filter algorithm.The core of the algorithm is to use new measurements to update multiple states in the past to compensate for the delay.The simulation results of the integrated navigation system of GNSS and INS show that the filtering algorithm designed in this paper can reduce the spike phenomenon after filtering and reduce the error of the estimation result when the measurement has a random delay.

关 键 词：组合导航 卡尔曼滤波 随机时延 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TJ761.1[自动化与计算机技术—计算机科学与技术]