北斗/微惯导组合导航方法研究
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摘要
随着我国北斗卫星导航系统建设的稳步推进和惯性导航技术的飞速发展,以及我军制导弹药发展的迫切需求,北斗/微惯导组合导航方法及相关应用技术已成为研究热点。本文利用软件接收机概念,构建北斗/微惯导组合导航系统,研究了基于软件接收机的紧组合与深组合导航框架,对于两类框架中的主要关键技术进行了优化设计,并对主要理论问题和方法进行了研究。论文的主要工作与创新点如下:
1.考虑SINS运动相关性条件下,从理论上进行软件接收机信号捕获与SINS的适配性分析。通过对软件接收机原理的分析,研究了基于软件接收机的BD-2/SINS组合导航方法框架;在此基础上,根据SINS辅助卫星信号捕获原理,深入分析了影响信号捕获性能的主要因素,利用SINS速度误差方程,推导了SINS性能与信号捕获性能之间的关系;针对载体高动态运动轨迹,分析了采用不同精度的SINS辅助对提高信号捕获性能的贡献;仿真结果表明,采用由100 deg/h精度的微陀螺和1 mg精度的微加速度计组成的低精度SINS辅助捕获卫星信号,在120 s内捕获灵敏度可以提高约4.2 dB-Hz。
2.研究了基于软件接收机的BD-2/MIMU紧组合导航方法。从理论上证明了表征卫星导航系统卫星几何分布特性的GDOP下界,对比分析了BD-2与GPS两系统的GDOP分布;针对BD-2系统包含三类轨道卫星的特点,提出了高动态条件下MIMU辅助快速选星算法,实验验证了算法的有效性;在紧组合导航方法框架下,设计了MIMU辅助环路跟踪条件下的紧组合导航算法,得出了在高动态情况下MIMU辅助的三阶PLL环路带宽为3 Hz时可保持环路锁定的结论;针对卫星信号缺失情况,提出了ANFIS辅助KF的紧组合导航算法,实验表明该算法在卫星信号失锁100 s内,仍能保持位置、速度精度不降低。
3.研究了基于软件接收机的BD-2/MIMU深组合导航方法。引入了半参数模型及广义补偿最小二乘估计的基本理论,阐述了正则矩阵与光滑因子的选取方式;针对MIMU系统误差较大的问题,在建立陀螺仪温度模型的基础上,针对陀螺仪启动过程的误差补偿问题,提出了半参数模型的系统误差建模与补偿算法;针对MIMU的随机误差,研究了基于AR(2)模型的推广递推最小二乘算法;实验验证了上述两个算法的可行性和有效性;研究了深组合导航算法的总体结构,采用序贯滤波方法设计了深组合导航滤波器,对矢量跟踪环结构进行了设计;针对矢量跟踪环结构中的基带信号预处理模块,研究了基于半参数模型的多项式拟合算法。
4.研制了基于软件接收机的BD-2/MIMU组合导航原理样机。利用北斗卫星信号模拟器及相关实验条件,结合实际的高动态飞行数据,设计了实验方案;对于真实轨迹驱动产生的BD-2模拟卫星信号进行了捕获实验,结果表明采用预检测积分5 ms时,能够成功捕获信号;从实验的角度阐述了紧组合与深组合方式的导航精度测试方案,对关键技术指标进行了评测,结果表明,整体上深组合导航精度稍优于紧组合导航,两种导航方法的位置精度优于6 m,速度精度优于0.15 m/s,水平姿态角优于0.4 deg,航向角精度优于0.5 deg。
5.研究了基于神经网络辅助卡尔曼滤波的BD-1/SINS组合导航方法。针对BD-1有源定位带来的时间延迟问题,在理论上分析了神经网络辅助卡尔曼滤波算法的有效性;构建了BD-1/SINS组合导航原理样机,车载实验结果表明,算法提高了定位精度,特别是在卫星信号暂时失锁情况下,性能改善更为明显,水平定位精度优于50 m。
Methods and application technology for BD/MIMU integrated navigation have been an attractive research with the developments of Beidou satellites navigation system in China and inertial navigation technology and our army in urgent need of technology for guided munitions. This thesis proposes a BD/MIMU integrated navigation system using the concept of software based receiver technique, studies on tightly and deeply integrated frames and related optimization technologies. Some major theoretic problems and related key technologies are researched. The main contributions include the following aspects:
1. Considering the motion dependence of SINS performance, performance matching between software based receiver and SINS is analysed in theory. BD-2/SINS integration frame is established based on software based receiver. The principle of SINS aided satellites signal acquisition is presented and the influences factors are summarized detail by detail. The equations of performances between BD-2 receivers and SINS are induced using SINS velocity errors equations. Performance analysis of SINS aided acquisition based on motion dependence of SINS is evaluated in the high dynamic situation. Simulation experiments illustrate that aided acquisition method with SINS composed of 100 deg/h bias drift MEMS gyros and 1 mg bias drift MEMS accelerometers can enhance the sensitivity of probability of detection up to 4.2 dB-Hz compared with unaided acquisition.
2. A BD-2/MIMU tight integration algorithm based on software based receivers is proposed. The minimal GDOP value in theory which is a token of GNSS satellites distribution conditions is proved and GDOP comparison of BD-2 and GPS is analysed. A MIMU-aided rapid satellite selection algorithm in application to high dynamic conditions is proposed and its validity is proved by experimental results. The optimal loop bandwidth of MIMU-aided PLL was designed in the tightly integrated navigation algorithm based on a 3rd order PLL with 3 Hz loop bandwidth. In order to overcome the outages of satellites signals, an ANFIS aided KF tightly integrated algorithm is provided and experiments illustrate that the new algorithm can improve the performance of integrated system effectively and enhance the position accuracy even with 100 s outages of satellites signals.
3. A BD-2/MIMU deep integration algorithm based on software based receivers is presented. The principle of seimparametric regression model and penalized lest square method are introduced, and the choices of regular matrix and smoothing factor are discussed. Based on temperature compensation model of MEMS gyro, a seimparametric regression model of systemic errors compensation during the process of start-up is proposed to improve the performance of MEMS gyro accuracy. A gyro de-noising algorithm based on extended Recursive Least Square with AR(2) model are used to compensate gyro random drifts and related experiments prove the feasibility and effectiveness of new algorithms. Deep integration is discussed and filters are designed using cascading filtering technology. Vector-tracking structure is adopted and a seimparametric regression model for the pre-processing function of baseband signals is also researched to improve the performance of signals pre-processing.
4. A BD-2/MIMU integrated navigation system based on software based recerivers is set up. Test methods are designed with real high dynamic flight data grounded on conditions of our lab and BD signals simulator. Satellites signals acquisition tests are carried out and signals can acquisited successfully using 5 ms pre-detection integration time. Tighly integrated method and deeply integrated method are applied to this BD-2/MIMU navigation system. The test results show that two methods are feasible and the positioning accuracy is better than 6 m and velocity accuracy is better than 0.15 m/s, the horizontal attitude accuracy is better than 0.4 degrees and the yaw accuracy is better than 0.5 degrees.
5. A BD-1/SINS integrated navigation system is presented. A back-propagation neural network aided KF algorithm is proposed in order to overcome the time delay of BD-1 positioning. The algorithm has been verified on real data collected in land vehicle tests and is compared with other approaches, especially with the outages of satellites signals. The results demonstrate that the new algorithm improves the horizontal positioning accuracy with better than 50 m.
1.考虑SINS运动相关性条件下,从理论上进行软件接收机信号捕获与SINS的适配性分析。通过对软件接收机原理的分析,研究了基于软件接收机的BD-2/SINS组合导航方法框架;在此基础上,根据SINS辅助卫星信号捕获原理,深入分析了影响信号捕获性能的主要因素,利用SINS速度误差方程,推导了SINS性能与信号捕获性能之间的关系;针对载体高动态运动轨迹,分析了采用不同精度的SINS辅助对提高信号捕获性能的贡献;仿真结果表明,采用由100 deg/h精度的微陀螺和1 mg精度的微加速度计组成的低精度SINS辅助捕获卫星信号,在120 s内捕获灵敏度可以提高约4.2 dB-Hz。
2.研究了基于软件接收机的BD-2/MIMU紧组合导航方法。从理论上证明了表征卫星导航系统卫星几何分布特性的GDOP下界,对比分析了BD-2与GPS两系统的GDOP分布;针对BD-2系统包含三类轨道卫星的特点,提出了高动态条件下MIMU辅助快速选星算法,实验验证了算法的有效性;在紧组合导航方法框架下,设计了MIMU辅助环路跟踪条件下的紧组合导航算法,得出了在高动态情况下MIMU辅助的三阶PLL环路带宽为3 Hz时可保持环路锁定的结论;针对卫星信号缺失情况,提出了ANFIS辅助KF的紧组合导航算法,实验表明该算法在卫星信号失锁100 s内,仍能保持位置、速度精度不降低。
3.研究了基于软件接收机的BD-2/MIMU深组合导航方法。引入了半参数模型及广义补偿最小二乘估计的基本理论,阐述了正则矩阵与光滑因子的选取方式;针对MIMU系统误差较大的问题,在建立陀螺仪温度模型的基础上,针对陀螺仪启动过程的误差补偿问题,提出了半参数模型的系统误差建模与补偿算法;针对MIMU的随机误差,研究了基于AR(2)模型的推广递推最小二乘算法;实验验证了上述两个算法的可行性和有效性;研究了深组合导航算法的总体结构,采用序贯滤波方法设计了深组合导航滤波器,对矢量跟踪环结构进行了设计;针对矢量跟踪环结构中的基带信号预处理模块,研究了基于半参数模型的多项式拟合算法。
4.研制了基于软件接收机的BD-2/MIMU组合导航原理样机。利用北斗卫星信号模拟器及相关实验条件,结合实际的高动态飞行数据,设计了实验方案;对于真实轨迹驱动产生的BD-2模拟卫星信号进行了捕获实验,结果表明采用预检测积分5 ms时,能够成功捕获信号;从实验的角度阐述了紧组合与深组合方式的导航精度测试方案,对关键技术指标进行了评测,结果表明,整体上深组合导航精度稍优于紧组合导航,两种导航方法的位置精度优于6 m,速度精度优于0.15 m/s,水平姿态角优于0.4 deg,航向角精度优于0.5 deg。
5.研究了基于神经网络辅助卡尔曼滤波的BD-1/SINS组合导航方法。针对BD-1有源定位带来的时间延迟问题,在理论上分析了神经网络辅助卡尔曼滤波算法的有效性;构建了BD-1/SINS组合导航原理样机,车载实验结果表明,算法提高了定位精度,特别是在卫星信号暂时失锁情况下,性能改善更为明显,水平定位精度优于50 m。
Methods and application technology for BD/MIMU integrated navigation have been an attractive research with the developments of Beidou satellites navigation system in China and inertial navigation technology and our army in urgent need of technology for guided munitions. This thesis proposes a BD/MIMU integrated navigation system using the concept of software based receiver technique, studies on tightly and deeply integrated frames and related optimization technologies. Some major theoretic problems and related key technologies are researched. The main contributions include the following aspects:
1. Considering the motion dependence of SINS performance, performance matching between software based receiver and SINS is analysed in theory. BD-2/SINS integration frame is established based on software based receiver. The principle of SINS aided satellites signal acquisition is presented and the influences factors are summarized detail by detail. The equations of performances between BD-2 receivers and SINS are induced using SINS velocity errors equations. Performance analysis of SINS aided acquisition based on motion dependence of SINS is evaluated in the high dynamic situation. Simulation experiments illustrate that aided acquisition method with SINS composed of 100 deg/h bias drift MEMS gyros and 1 mg bias drift MEMS accelerometers can enhance the sensitivity of probability of detection up to 4.2 dB-Hz compared with unaided acquisition.
2. A BD-2/MIMU tight integration algorithm based on software based receivers is proposed. The minimal GDOP value in theory which is a token of GNSS satellites distribution conditions is proved and GDOP comparison of BD-2 and GPS is analysed. A MIMU-aided rapid satellite selection algorithm in application to high dynamic conditions is proposed and its validity is proved by experimental results. The optimal loop bandwidth of MIMU-aided PLL was designed in the tightly integrated navigation algorithm based on a 3rd order PLL with 3 Hz loop bandwidth. In order to overcome the outages of satellites signals, an ANFIS aided KF tightly integrated algorithm is provided and experiments illustrate that the new algorithm can improve the performance of integrated system effectively and enhance the position accuracy even with 100 s outages of satellites signals.
3. A BD-2/MIMU deep integration algorithm based on software based receivers is presented. The principle of seimparametric regression model and penalized lest square method are introduced, and the choices of regular matrix and smoothing factor are discussed. Based on temperature compensation model of MEMS gyro, a seimparametric regression model of systemic errors compensation during the process of start-up is proposed to improve the performance of MEMS gyro accuracy. A gyro de-noising algorithm based on extended Recursive Least Square with AR(2) model are used to compensate gyro random drifts and related experiments prove the feasibility and effectiveness of new algorithms. Deep integration is discussed and filters are designed using cascading filtering technology. Vector-tracking structure is adopted and a seimparametric regression model for the pre-processing function of baseband signals is also researched to improve the performance of signals pre-processing.
4. A BD-2/MIMU integrated navigation system based on software based recerivers is set up. Test methods are designed with real high dynamic flight data grounded on conditions of our lab and BD signals simulator. Satellites signals acquisition tests are carried out and signals can acquisited successfully using 5 ms pre-detection integration time. Tighly integrated method and deeply integrated method are applied to this BD-2/MIMU navigation system. The test results show that two methods are feasible and the positioning accuracy is better than 6 m and velocity accuracy is better than 0.15 m/s, the horizontal attitude accuracy is better than 0.4 degrees and the yaw accuracy is better than 0.5 degrees.
5. A BD-1/SINS integrated navigation system is presented. A back-propagation neural network aided KF algorithm is proposed in order to overcome the time delay of BD-1 positioning. The algorithm has been verified on real data collected in land vehicle tests and is compared with other approaches, especially with the outages of satellites signals. The results demonstrate that the new algorithm improves the horizontal positioning accuracy with better than 50 m.
引文
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