基于卡尔曼滤波的无人机组合导航系统设计  

Design of a GPS-aided INS Based on Kalman Filter

作　　者：王浩[1] 黄长强[1] 吴文超[1] 

机构地区：[1]空军工程大学工程学院,陕西西安710038

出　　处：《计算机仿真》2009年第4期31-33,124,共4页Computer Simulation

基　　金：军队重点科研项目基金(KJ06703);空军工程大学工程学院优秀博士学位论文创新基金资助(BC06003)

摘　　要：针对卡尔曼滤波在实际应用中遇到的系统通常不是严格线性的问题,改进了在组合导航系统中常用的卡尔曼滤波方法,用扩展卡尔曼滤波对INS和外部测量源的信息进行融合,推导了无人机GPS辅助惯性导航系统的导航方程。通过分析GPS和INS的定位原理,建立了GPS和INS的误差模型。完成了以INS为主导航系统,GPS作为辅助系统的组合导航系统的扩展卡尔曼滤波设计。最后,将线性卡尔曼滤波和扩展卡尔曼滤波的结果进行了仿真对比分析,结果表明:扩展卡尔曼滤波更适合系统为非线性的情况。The common Kalman filtering method used for integrated navigation was updated in order to solve the nonlinear problem of the system function. Extended Kalman filtering was used to fuse information from INS and other aided source and navigation function of UAV. The principles of GPS and INS navigation were analyzed. Error models of GPS and INS were constructed then. An extended Kalman filter for the GPS aided INS was designed. The performance of extended Kalman filter was compared with linear Kalman filters finally. The result shows that the extended Kalman filter is more fit for nonlinear systems.

关 键 词：扩展卡尔曼滤波 组合导航 误差模型 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计]