SINS/GPS组合导航系统Kalman滤波仿真研究
|
摘要
为克服捷联惯导系统SINS误差随时间积累、长期精度差和全球定位系统GPS易失锁、不易实时控制的缺点,本文研究了SINS和GPS的原理,在惯导误差分析的基础上,同时考虑SINS/GPS组合导航的杆臂误差和时间不同步误差,建立以速度和位置误差为观测量的SINS/GPS系统状态空间模型和观测方程;采用扩展卡尔曼滤波EKF算法对SINS/GPS的组合系统进行信息融合。Matlab仿真结果表明,本文建立的模型组合导航提高了定位精度。
The error of the Strapdown Inertial Navigation System(SINS)accumulates over time and its long-term accuracy is poor,also Global positioning system(GPS)is easily unlock and has poor real time control performance.In order to overcome these shortcomings,the principles of SINS and GPS are researched.Based on the analysis of inertial navigation error,considering the arm error and time unsynchronization error of SINS/GPS integrated navigation,the state space model and observation equation of SINS/GPS system based on velocity and position error are established.The extended Kalman filter EKF algorithm is used to integrate the SINS/GPS combination system.The simulation results of Matlab show that the model established in this paper is correct,and the integrated navigation greatly improves the positioning accuracy.
The error of the Strapdown Inertial Navigation System(SINS)accumulates over time and its long-term accuracy is poor,also Global positioning system(GPS)is easily unlock and has poor real time control performance.In order to overcome these shortcomings,the principles of SINS and GPS are researched.Based on the analysis of inertial navigation error,considering the arm error and time unsynchronization error of SINS/GPS integrated navigation,the state space model and observation equation of SINS/GPS system based on velocity and position error are established.The extended Kalman filter EKF algorithm is used to integrate the SINS/GPS combination system.The simulation results of Matlab show that the model established in this paper is correct,and the integrated navigation greatly improves the positioning accuracy.
引文
[1] 严恭敏.捷联惯导算法及车载组合导航系统研究[D].西安:西北工业大学,2004.
[2] 刘培伟.GPS/SINS组合导航系统仿真研究[D].长春:长春工业大学,2010.
[3] 杜尚丰,宫晓琳.GPS/SINS综合定位系统仿真实验研究[J].仪器仪表学报,2005,26(8):425-426.
[4] 秦永元.惯性导航[M].北京:科学出版社,2006.
[5] 徐成龙.基于多传感器融合水下机器人(AUV)导航方法的研究[D].沈阳:东北大学,2017.
[6] 员丽琼,景占荣.SINS/GPS组合导航系统Kalman滤波仿真研究[J].自动化仪表,2011,32(1):67-72.
[7] Jia B,Xin M,Cheng Y.High-degree cubature Kalmanfilter[J].Automatic,2013,49(2):510-518.
[8] 苗岳旺.SINS/GPS组合导航数据处理方法研究[D].郑州:解放军信息工程大学,2013.
[9] 秦永元.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,2004.
[10] Han S L,Wang J L.Quantization and Colored Noises Error Modeling for Tnertial Sensors for GPS/INS Integration[J].IEEE SENSORS JOURNAL.2011,11(6):1493-1503.
[2] 刘培伟.GPS/SINS组合导航系统仿真研究[D].长春:长春工业大学,2010.
[3] 杜尚丰,宫晓琳.GPS/SINS综合定位系统仿真实验研究[J].仪器仪表学报,2005,26(8):425-426.
[4] 秦永元.惯性导航[M].北京:科学出版社,2006.
[5] 徐成龙.基于多传感器融合水下机器人(AUV)导航方法的研究[D].沈阳:东北大学,2017.
[6] 员丽琼,景占荣.SINS/GPS组合导航系统Kalman滤波仿真研究[J].自动化仪表,2011,32(1):67-72.
[7] Jia B,Xin M,Cheng Y.High-degree cubature Kalmanfilter[J].Automatic,2013,49(2):510-518.
[8] 苗岳旺.SINS/GPS组合导航数据处理方法研究[D].郑州:解放军信息工程大学,2013.
[9] 秦永元.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,2004.
[10] Han S L,Wang J L.Quantization and Colored Noises Error Modeling for Tnertial Sensors for GPS/INS Integration[J].IEEE SENSORS JOURNAL.2011,11(6):1493-1503.