GPS/SINS深度组合导航系统研究
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摘要
捷联惯性导航系统(SINS,Strap-down Inertial Navigation System)、全球定位系统(GPS, Global Positioning System)各有其特点。GPS/SINS组合,性能互补,是高度自主性和高精度导航的重要方案。基于伪距、伪距率的GPS/SINS深度组合导航系统相对于基于速度、位置的组合导航系统具有更高的导航精度、更好的鲁棒性、抗干扰性。论文主要研究深度组合导航滤波模型,利用SINS辅助GPS在可见星不足情况下实现定位。同时利用SINS判断出多路径效应,消除多路径效应的影响,实现高精度的定位。
论文首先简单阐述了导航系统的发展概况,GPS/SINS组合导航系统的特点,国内外深度组合的发展现状,以及组合导航系统的信息融合理论;分别对组合导航子系统(GPS和捷联惯性导航系统)的原理和误差进行分析,并且介绍了多路径效应的原理,产生原因和常见消弱多路径效应的方法。
其次,以GPS系统和捷联惯导系统误差方程为基础,建立深度组合导航系统误差模型,设计出GPS/SINS深度组合仿真系统。研究深度组合导航中的信息融合技术,重点研究了离散卡尔曼滤波、自适应卡尔曼滤波和平淡卡尔曼滤波方法,并对不同滤波方法的定位精度进行比较。从仿真结果中看出,平淡卡尔曼滤波的精度最高,因此选择平淡卡尔曼滤波作为深度组合导航系统的滤波模型。
然后,在GPS可见星不足的情况下,利用SINS辅助定位,通过设计的实验比较,发现在可见星不足(3颗星)的情况下,GPS/SINS深度组合模型能够实现短暂的精确定位。
最后,利用SINS辅助判断多路径效应,通过SINS推算出下一时刻的伪距、伪距率。通过对伪距、伪距率范围的确定,可以判定受到多路径效应影响的卫星。在定位解算时,去除此颗卫星,用GPS/SINS深度组合导航系统模型,消除多路径效应的影响,实现高精度的定位。
GPS (Global Positioning System) satellite navigation system, strap-down inertial navigation system (SINS) each has its traits. Integrating GPS, SINS and complementing their performance is important scheme for highly autonomous and accurate navigation. Deep integrated GPS/SINS system based on pseudo-range and pseudo-range rate is more accurate, robust, jam-resistant than the loosely coupled model based on position and velocity. The thesis mainly research the filter model of deep coupled navigation system .Based on this model, SINS is used to assist position calculation of GPS when less than 4 satellites in sight. In the meanwhile, SINS is used to determine the multipath effect and eliminate the multipath effect to reach high precision.
Firstly, a brief review of the development of navigation system and the characteristics of integrated navigation system, then the present situation of deep integrated system and the theory of the data fusion of integrated navigation system are discussed. The principles, error models and characteristics of different navigation systems, including Strap-down Inertial Navigation System (SINS), Global Positioning System (GPS) are also introduced. Then the principle, reason of multi-path effect and some normal ways to eliminate it are also introduced.
Secondly, error model of deep integrated navigation system is build based on the error equation of GPS and SINS and the simulation system of deep integrated GPS/SINS system is designed. Then, the data fusion technology of deep integrated navigation system is researched. Discrete Kalman Filter, Adaptive Filter and Unscented Kalman Filter (UKF) are used in the system. After the comparison of different filter models, the best precision filter model is used in the deep integrated navigation system below. Thirdly, SINS is used to assist the position calculation of GPS when less than 4 satellites insight. Experiment results show that the deep integrated GPS/SINS system can realize high precision positioning in a short time.
Finally, SINS is used to determine the multi-path effect .Pseudo-range and pseudo-range rate can be calculated by SINS. The satellite which suffered from multi-path effect can be determined by judging the reasonable range of pseudo-range and pseudo-range rate. Then, the satellite suffered from multi-path effect is not used in the position calculation. Experiment results shows that the method can effectively eliminate the multi-path effect and get high precision position information.
论文首先简单阐述了导航系统的发展概况,GPS/SINS组合导航系统的特点,国内外深度组合的发展现状,以及组合导航系统的信息融合理论;分别对组合导航子系统(GPS和捷联惯性导航系统)的原理和误差进行分析,并且介绍了多路径效应的原理,产生原因和常见消弱多路径效应的方法。
其次,以GPS系统和捷联惯导系统误差方程为基础,建立深度组合导航系统误差模型,设计出GPS/SINS深度组合仿真系统。研究深度组合导航中的信息融合技术,重点研究了离散卡尔曼滤波、自适应卡尔曼滤波和平淡卡尔曼滤波方法,并对不同滤波方法的定位精度进行比较。从仿真结果中看出,平淡卡尔曼滤波的精度最高,因此选择平淡卡尔曼滤波作为深度组合导航系统的滤波模型。
然后,在GPS可见星不足的情况下,利用SINS辅助定位,通过设计的实验比较,发现在可见星不足(3颗星)的情况下,GPS/SINS深度组合模型能够实现短暂的精确定位。
最后,利用SINS辅助判断多路径效应,通过SINS推算出下一时刻的伪距、伪距率。通过对伪距、伪距率范围的确定,可以判定受到多路径效应影响的卫星。在定位解算时,去除此颗卫星,用GPS/SINS深度组合导航系统模型,消除多路径效应的影响,实现高精度的定位。
GPS (Global Positioning System) satellite navigation system, strap-down inertial navigation system (SINS) each has its traits. Integrating GPS, SINS and complementing their performance is important scheme for highly autonomous and accurate navigation. Deep integrated GPS/SINS system based on pseudo-range and pseudo-range rate is more accurate, robust, jam-resistant than the loosely coupled model based on position and velocity. The thesis mainly research the filter model of deep coupled navigation system .Based on this model, SINS is used to assist position calculation of GPS when less than 4 satellites in sight. In the meanwhile, SINS is used to determine the multipath effect and eliminate the multipath effect to reach high precision.
Firstly, a brief review of the development of navigation system and the characteristics of integrated navigation system, then the present situation of deep integrated system and the theory of the data fusion of integrated navigation system are discussed. The principles, error models and characteristics of different navigation systems, including Strap-down Inertial Navigation System (SINS), Global Positioning System (GPS) are also introduced. Then the principle, reason of multi-path effect and some normal ways to eliminate it are also introduced.
Secondly, error model of deep integrated navigation system is build based on the error equation of GPS and SINS and the simulation system of deep integrated GPS/SINS system is designed. Then, the data fusion technology of deep integrated navigation system is researched. Discrete Kalman Filter, Adaptive Filter and Unscented Kalman Filter (UKF) are used in the system. After the comparison of different filter models, the best precision filter model is used in the deep integrated navigation system below. Thirdly, SINS is used to assist the position calculation of GPS when less than 4 satellites insight. Experiment results show that the deep integrated GPS/SINS system can realize high precision positioning in a short time.
Finally, SINS is used to determine the multi-path effect .Pseudo-range and pseudo-range rate can be calculated by SINS. The satellite which suffered from multi-path effect can be determined by judging the reasonable range of pseudo-range and pseudo-range rate. Then, the satellite suffered from multi-path effect is not used in the position calculation. Experiment results shows that the method can effectively eliminate the multi-path effect and get high precision position information.
引文
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[32]陈莉,自适应滤波算法与应用研究[硕士论文],西安电子科技大学,2006
[33]李丽锦,基于自适应卡尔曼滤波的捷联惯导非线性对准技术研究[硕士论文],2006
[33]卞鸿巍等,组合导航智能信息融合自适应滤波算法分析,系统工程与电子技术,2004年10月,第26卷第10期:1449-1453
[34]王永刚等,改进Sage-Husa滤波及在GPS/INS容错组合制导中的应用,中国惯性技术学报,2003年10月,第11卷第5期:29-32
[35]张翔,一种变步长LMS自适应滤波算法研究,航空计算技术,2004年3月,第34卷第1期:9-12
[36]徐凯等,一种改进的变步长自适应滤波器LMS算法,电路与系统学报,2004年8月,第9卷第4期:115-117
[37]王敏强等,一种新的可变步长LMS自适应滤波算法,信号处理,2004年12月,第20卷第6期:613-617
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[40]王淑一,程杨,杨涤,崔祜涛.UKF方法及其在方位跟踪问题中的应用[J].飞行力学, 2003 , 21 (2) : 59-62.
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[2]杜习奇,GPS与捷联惯导组合导航系统研究[硕士论文],南京:南京理工大学,2004
[3]帅平,GPS/SINS组合导航系统理论与实现技术研究[博士论文],北京:中国航天科工集团第二研究院,2002
[4]张树侠,孙静,捷联式惯性导航系统,北京,国防工业出版社,1992,1-78
[5]陈哲,捷联惯导系统原理,北京,宇航出版社,1986,1-223
[6]刘利生,吴斌,曹坤梅,刘元,卫星导航测量差分自校准融合技术,北京,国防工业出版社,2006,1-4
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[8]孙枫,袁赣南,张晓红.组合导航系统.哈尔滨:哈尔滨工程技术大学出版社,1996.12.
[9]D.A.Tazartes and J.G.Mark.Integration of GPS Receiver into Existing Inertial Navigation System[J].Navigation:Journal of the Institute of Navigation,1988,35(1):105-119.
[10]P.W.Ward and M.Jeerage.The Texas Instruments/Honeywell GPS Guidance Package[C].Proceedings of the Position,Location and Navigation Symposium.IEEE,1992,pp.298-305.
[11]孙道省.嵌入式GPS/INS深组合导航系统研究[D].北京:航天科工集团第三研究院,1996
[12]栗瑞江.低成本SINS/GPS组合导航系统研究[D].西安:西北工业大学,2003
[13]李方锁,孙道省.嵌入式深组合导航系统的研究与应用[J].战术导弹控制技术.2 00 0,33(2):42-47
[14]刘基余,GPS卫星导航定位原理与方法,北京,科学出版社,2003,1-204
[15]王惠南,GPS导航原理与应用,北京,科学出版社,2003
[16] Yun chun, Yang. Tightly Integrated Attitude Determination Methods for Low–Cost Inertial Navigation: Two-Antenna GPS and GPS/Magnetometer Dissertation for the Doctor Degree in Electrical Engineering. University of California,Riverside,2001
[17]刘基余,等.全球定位系统原理及其应用[M].北京:测绘出版社,1993
[18] Jayanta Kumar Ray. Mitigation of GPS code and carrier phase multipatheffects using a multi-antenna system[D].The University of Calgary,2000
[19]魏子卿,等. GPS相对定位的数学模型.北京:测绘出版社, 1998.
[20]谢世杰.论GPS测量中的多路径误差.见: GPS技术应用论文集.中国GPS协会筹委会办公室, 1995.
[21]Gunter, Seeber.赖锡安等译.卫星大地测量学.北京:地震出版社, 1998.
[22]过静君,等.多路径效应对GPS定位影响的研究.工程勘察, 1995 (2).
[23]Heister H. M ult ipath - einflup bei GPS phasenmessungen ausw irkung and konsequenzen fur p rakfischemessungen. AVN , 1997, 5.
[24]杨艳娟,捷联惯性导航系统关键技术研究[博士论文],哈尔滨,哈尔滨工程大学,2001
[25]袁信,郑谔,捷联式惯性导航原理,北京,航空专业教材编审组,1985,1-150
[26]丁衡高,惯性技术文集,北京,国防工业出版社,1994,10-29
[27]刘小光,谢玲,戴亚平等,捷联式惯性导航系统误差处理技术的新进展[J],火力与指挥控制,2001,26(4):259-262
[28]高新闻,陈孝威,捷联惯性测量系统的误差补偿研究[J],贵州大学学报,2003,20(2):
[29]张男,王莹,张尔扬,GPS/INS组合导航系统设计及实现方案[J],遥感技术与应用,2002,17(2)
[30]江泽,INS/GPS实时仿真系统研究[硕士论文],西北工业大学,2003
[31]陈帅,薛晓中,吴参林,孙瑞胜,SINS/GPS组合导航仿真系统研究[J],计算机仿真,2007,24(4)
[32]陈莉,自适应滤波算法与应用研究[硕士论文],西安电子科技大学,2006
[33]李丽锦,基于自适应卡尔曼滤波的捷联惯导非线性对准技术研究[硕士论文],2006
[33]卞鸿巍等,组合导航智能信息融合自适应滤波算法分析,系统工程与电子技术,2004年10月,第26卷第10期:1449-1453
[34]王永刚等,改进Sage-Husa滤波及在GPS/INS容错组合制导中的应用,中国惯性技术学报,2003年10月,第11卷第5期:29-32
[35]张翔,一种变步长LMS自适应滤波算法研究,航空计算技术,2004年3月,第34卷第1期:9-12
[36]徐凯等,一种改进的变步长自适应滤波器LMS算法,电路与系统学报,2004年8月,第9卷第4期:115-117
[37]王敏强等,一种新的可变步长LMS自适应滤波算法,信号处理,2004年12月,第20卷第6期:613-617
[38]Julier S J, Uhlmann J K and Durrant Whyte H. A New Approach for Filtering Nonlinear Systems [C] Proceedings of the American Control Conference, Washington , 1995 : 1628-1632.
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