组合导航系统多源信息融合关键技术研究
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摘要
组合导航系统是用以解决导航定位、运动控制、设备标定对准等问题的信息综合系统，具有高精度、高可靠性、高自动化程度的优点，是网络化导航系统发展的必然趋势。从本质上看，组合导航系统是多传感器多源导航信息的集成优化融合系统，它的核心技术是信息的融合和处理。信息融合的核心问题可以归结为三类问题：数据问题，方法问题和模型问题。信息融合系统要达到其设计要求，要完成其任务与使命，要实现其工作目的，都必须面对相应对象条件下的数据、方法和模型。
论文以某型水下载体组合导航系统设计为技术背景，围绕多源信息融合中的三类问题，针对组合导航系统的相关技术热点，提出了组合导航系统的信息融合结构，并在传感器时空配准、自适应联邦滤波及其最优性分析、导航多模型融合等关键问题上开展研究。
1针对多传感器系统导航信息时空属性不一致的问题，明确了在组合导航系统中时间配准和空间配准的任务，分别分析了组合导航系统中时间误差和空间误差的来源与影响；分析了现有时间配准方法在多传感器系统中的局限性，提出一种基于分段重叠的时间配准算法，通过分段重叠处理，在保证量测精度的条件下将不同传感器的量测信息配准到统一处理时刻，抑制了具有不确定性的时间误差；提出异步融合条件下的改进非等间隔联邦滤波算法，解决非等间隔滤波算法无法适用测量周期有较大倍率的工程情况的问题，增加融合信息，扩大算法适用性和实用性，使改进算法工程化；对导航中的坐标系转换的问题进行统一的数学描述；在分析杆臂效应在惯导系统中的作用机理和低通滤波法处理杆臂加速度的基础上，针对组合导航系统多传感器之间杆臂效应影响速度估计的问题，通过反向推导杆臂加速度原理分析杆臂效应在速度估计中的作用，提出用杆臂误差简易模型补偿速度估计的方法。
2以联邦滤波作为组合导航系统基础融合估计算法，归纳总结联邦滤波中系统方程的不同建立方法，并按照工程需要建立INS/ESGM/GPS/LNC/TAN/DVL组合导航系统的系统方程，通过基于奇异值分解的可观测性分析方法预测系统方程的合理性和验证组合系统的优越性；针对联邦滤波信息分配原则研究中相互矛盾的现状，通过归纳、对比，以信息分配系数与系统性能的关系为研究对象，根据联邦滤波理论分析得出关于信息分配原则的三个结论，为联邦滤波设计提供理论依据；针对现有联邦滤波自适应改进的信息源从滤波处理本身信息出发的不足，提出了基于时间序列分析的自适应联邦滤波算法，利用导航传感器的历史数据，通过时间序列分析得出信息平滑程度，以此调整信息分配系数，使系统结构更加适应系统真实情况，提高滤波精度、数据平稳性和信息利用率。
3从估计的本质和估计最优性的内在性质出发，对组合导航系统信息融合估计方法的最优性进行分析。以线性最小方差作为最优准则，采用理论分析和实验分析的办法，对非理想条件下的融合估计的最优性进行了分析，分别对有色噪声情况下的Kalman滤波、噪声相关情况下的Kalman滤波和传感器噪声相关情况下的分散滤波、估计相关情况下的联邦滤波、不同结构的联邦滤波、系统方程不同维数情况下的联邦滤波的最优性进行了分析；对基于时间序列分析的自适应联邦滤波的最优性进行了分析，通过分析自适应联邦滤波在理想条件下的最优性，以及在对非理想条件下估计最优性分析的基础上分析非理想条件下自适应联邦滤波的最优性，证明自适应改进不影响联邦滤波的最优性。
4将多模型理论引入组合导航系统中，研究将多模型理论应用于组合导航系统的方法，研究了以多模型自适应估计作为处理工具的解析冗余导航系统，分析了组合导航系统两种冗余方式，并设计了DR/INS冗余导航系统多模型自适应估计融合算法，保证载体拥有长时间航行的导航信息；针对模型变化误差造成融合估计不精确、长时间滤波发散的问题，提出了基于交互式多模型的改进联邦滤波算法，使用联邦滤波结构消除估计融合的相关性，在子滤波器中使用交互式多模型方法代替Kalman滤波，通过覆盖过程噪声方差阵和观测噪声方差阵的变化范围来抑制模型误差，提高滤波稳定性和抗干扰能力，保持系统性能在长时间航行中的稳定。
Integrated navigation system is the information integrated system used to solve theproblem of navigation and positioning, motion control and equipment calibration alignment.It is the inevitable development trend of network navigation system because of its advantagesof high precision, high stability and high degree of automation. In essence, integratednavigation system is the optimization and fusion system of multi-sensor and multi-sourcenavigation information, whose key technique is the processing and fusion of information. Thecore issues of information fusion can be summarized into three categories: data issue, methodissue and model issue. In order to meet the design requirements, to complete the mandate andmission and to achieve the final purpose, information fusion systems must face the data,method and model of the corresponding object.
With the technical background of the design of an underwater vehicle integratednavigation system, and concerned with the three issues of multi-source information fusion, theintegrated navigation system information fusion structures is proposed. Sensor time andspatial registration, adaptive federated filter and its optimality analysis, multi-model fusionare researched in the paper, which are the related key technique for integrated navigationsystem.
1. To solve the problem that the time and spatial properties of multi-sensor systemnavigation information are inconsistent, time and spatial registration in integrated navigationsystem is represented clearly. And the source of the time errors and spatial errors and theireffects to the integrated navigation system are analyzed. To solve current time registrationmethod only in the specific condition cannot use in integrated navigation system, a timeregistration method based on segmentation overlap is proposed in the paper. The measurementinformation of the different sensors can be unified into the same time by segment processing.The effective sampling rate and the precision can be improved by overlapping thesegmentation areas. To solve the problem that non-interval federated filter algorithm is unableto suit the project situation with great differences between measurement cycles, an improvednon-interval federated filter algorithm is proposed under asynchronous fusion, which canincrease fusion information and expand the applicability and practicality of the algorithm.Unified mathematics description of the coordinate system transformation in navigation isgiven. According to the analysis of lever arm effect in Inertial navigation system (INS) andthe low-pass filter dealing with the acceleration of the lever arm, the lever arm effect in velocity estimation is obtained by reverse derivation of the lever arm acceleration principle.And the compensation method for velocity estimation by simple model of lever arm error isproposed to solve the effect on velocity estimate by lever arm between multi-sensors.
2. Different methods of establishing system equations of the federated filter aresummarized, which is the basic fusion estimation method in the integrated navigation systemin this thesis. The system equations of the INS/ESGM/GPS/LNC/TAN/DVL integratednavigation system are established, and their rationality is predicted by the observabilityanalysis method based on singular value decomposition. By summarizing and analyzingexisted contradictory information distribution principles in adaptive federated filters, and bestudying the relationship between information distribution coefficient and systemperformances, three theorems of information distribution principle are proposed by theoreticalanalysis based on the basic theory of federated filter, which can be used as theory evidence forfederated filter design. From the angle of information source, the problem of informationdistribution coefficient is researched, and a new self-adaptive federated filter algorithm basedon time series analysis is proposed in the paper. The history data of navigation sensors areconsidered and analyzed by autoregressive moving-average (ARMA) model, thus theinformation distribution coefficient is adjusted according to the working status andcircumstances. Simulation results show that higher information efficiency, higher precision,fault-tolerance and stability can be obtained.
3. According to the essence of estimate and the intrinsic property of estimate optimality,the optimality of information fusion estimation methods in integrated navigation system isanalyzed. The optimality of Kalman filter in the case of colored noise, Kalman filter in thecase of the correlated noise, decentralized filter in the case of correlated sensor noises,federated filter in the case of correlated estimate, federated filter in the case of differentstructures, and federated filter in the case of different dimensions, are analyzed by theoreticalanalysis and experimental analysis with the optimal rule of linear minimum variance. Thenthe optimality of self-adaptive federated filter based on time series analysis in ideal conditionsand non-ideal conditions are analyzed, which proves that adaptive improvement does notaffect the optimality of the federated filter.
4. The method about how to apply the multi-model theory to integrated navigationsystem is researched. The redundant navigation system based on multi-model adaptiveestimation method is researched in the paper, and two ways of analytical redundancynavigation system are analyzed. The multi-model adaptive estimation fusion algorithm inDR/INS redundant integrated navigation system is proposed to guarantee the long time navigation of underwater vehicle. To solve the fusion estimation inaccuracy and long-timefilter divergence caused by model errors, an improved federated filter based on interactivemulti-model is proposed, in which federated filter structure is used to eliminate the correlatedestimate, and interactive multi-model is used instead of Kalman filter. The model error isrestrained by covering the range of the process noise covariance matrix and measurementnoise covariance matrix. And the anti-interference and stability can be obtained when theunderwater vehicle sails in long time.
论文以某型水下载体组合导航系统设计为技术背景，围绕多源信息融合中的三类问题，针对组合导航系统的相关技术热点，提出了组合导航系统的信息融合结构，并在传感器时空配准、自适应联邦滤波及其最优性分析、导航多模型融合等关键问题上开展研究。
1针对多传感器系统导航信息时空属性不一致的问题，明确了在组合导航系统中时间配准和空间配准的任务，分别分析了组合导航系统中时间误差和空间误差的来源与影响；分析了现有时间配准方法在多传感器系统中的局限性，提出一种基于分段重叠的时间配准算法，通过分段重叠处理，在保证量测精度的条件下将不同传感器的量测信息配准到统一处理时刻，抑制了具有不确定性的时间误差；提出异步融合条件下的改进非等间隔联邦滤波算法，解决非等间隔滤波算法无法适用测量周期有较大倍率的工程情况的问题，增加融合信息，扩大算法适用性和实用性，使改进算法工程化；对导航中的坐标系转换的问题进行统一的数学描述；在分析杆臂效应在惯导系统中的作用机理和低通滤波法处理杆臂加速度的基础上，针对组合导航系统多传感器之间杆臂效应影响速度估计的问题，通过反向推导杆臂加速度原理分析杆臂效应在速度估计中的作用，提出用杆臂误差简易模型补偿速度估计的方法。
2以联邦滤波作为组合导航系统基础融合估计算法，归纳总结联邦滤波中系统方程的不同建立方法，并按照工程需要建立INS/ESGM/GPS/LNC/TAN/DVL组合导航系统的系统方程，通过基于奇异值分解的可观测性分析方法预测系统方程的合理性和验证组合系统的优越性；针对联邦滤波信息分配原则研究中相互矛盾的现状，通过归纳、对比，以信息分配系数与系统性能的关系为研究对象，根据联邦滤波理论分析得出关于信息分配原则的三个结论，为联邦滤波设计提供理论依据；针对现有联邦滤波自适应改进的信息源从滤波处理本身信息出发的不足，提出了基于时间序列分析的自适应联邦滤波算法，利用导航传感器的历史数据，通过时间序列分析得出信息平滑程度，以此调整信息分配系数，使系统结构更加适应系统真实情况，提高滤波精度、数据平稳性和信息利用率。
3从估计的本质和估计最优性的内在性质出发，对组合导航系统信息融合估计方法的最优性进行分析。以线性最小方差作为最优准则，采用理论分析和实验分析的办法，对非理想条件下的融合估计的最优性进行了分析，分别对有色噪声情况下的Kalman滤波、噪声相关情况下的Kalman滤波和传感器噪声相关情况下的分散滤波、估计相关情况下的联邦滤波、不同结构的联邦滤波、系统方程不同维数情况下的联邦滤波的最优性进行了分析；对基于时间序列分析的自适应联邦滤波的最优性进行了分析，通过分析自适应联邦滤波在理想条件下的最优性，以及在对非理想条件下估计最优性分析的基础上分析非理想条件下自适应联邦滤波的最优性，证明自适应改进不影响联邦滤波的最优性。
4将多模型理论引入组合导航系统中，研究将多模型理论应用于组合导航系统的方法，研究了以多模型自适应估计作为处理工具的解析冗余导航系统，分析了组合导航系统两种冗余方式，并设计了DR/INS冗余导航系统多模型自适应估计融合算法，保证载体拥有长时间航行的导航信息；针对模型变化误差造成融合估计不精确、长时间滤波发散的问题，提出了基于交互式多模型的改进联邦滤波算法，使用联邦滤波结构消除估计融合的相关性，在子滤波器中使用交互式多模型方法代替Kalman滤波，通过覆盖过程噪声方差阵和观测噪声方差阵的变化范围来抑制模型误差，提高滤波稳定性和抗干扰能力，保持系统性能在长时间航行中的稳定。
Integrated navigation system is the information integrated system used to solve theproblem of navigation and positioning, motion control and equipment calibration alignment.It is the inevitable development trend of network navigation system because of its advantagesof high precision, high stability and high degree of automation. In essence, integratednavigation system is the optimization and fusion system of multi-sensor and multi-sourcenavigation information, whose key technique is the processing and fusion of information. Thecore issues of information fusion can be summarized into three categories: data issue, methodissue and model issue. In order to meet the design requirements, to complete the mandate andmission and to achieve the final purpose, information fusion systems must face the data,method and model of the corresponding object.
With the technical background of the design of an underwater vehicle integratednavigation system, and concerned with the three issues of multi-source information fusion, theintegrated navigation system information fusion structures is proposed. Sensor time andspatial registration, adaptive federated filter and its optimality analysis, multi-model fusionare researched in the paper, which are the related key technique for integrated navigationsystem.
1. To solve the problem that the time and spatial properties of multi-sensor systemnavigation information are inconsistent, time and spatial registration in integrated navigationsystem is represented clearly. And the source of the time errors and spatial errors and theireffects to the integrated navigation system are analyzed. To solve current time registrationmethod only in the specific condition cannot use in integrated navigation system, a timeregistration method based on segmentation overlap is proposed in the paper. The measurementinformation of the different sensors can be unified into the same time by segment processing.The effective sampling rate and the precision can be improved by overlapping thesegmentation areas. To solve the problem that non-interval federated filter algorithm is unableto suit the project situation with great differences between measurement cycles, an improvednon-interval federated filter algorithm is proposed under asynchronous fusion, which canincrease fusion information and expand the applicability and practicality of the algorithm.Unified mathematics description of the coordinate system transformation in navigation isgiven. According to the analysis of lever arm effect in Inertial navigation system (INS) andthe low-pass filter dealing with the acceleration of the lever arm, the lever arm effect in velocity estimation is obtained by reverse derivation of the lever arm acceleration principle.And the compensation method for velocity estimation by simple model of lever arm error isproposed to solve the effect on velocity estimate by lever arm between multi-sensors.
2. Different methods of establishing system equations of the federated filter aresummarized, which is the basic fusion estimation method in the integrated navigation systemin this thesis. The system equations of the INS/ESGM/GPS/LNC/TAN/DVL integratednavigation system are established, and their rationality is predicted by the observabilityanalysis method based on singular value decomposition. By summarizing and analyzingexisted contradictory information distribution principles in adaptive federated filters, and bestudying the relationship between information distribution coefficient and systemperformances, three theorems of information distribution principle are proposed by theoreticalanalysis based on the basic theory of federated filter, which can be used as theory evidence forfederated filter design. From the angle of information source, the problem of informationdistribution coefficient is researched, and a new self-adaptive federated filter algorithm basedon time series analysis is proposed in the paper. The history data of navigation sensors areconsidered and analyzed by autoregressive moving-average (ARMA) model, thus theinformation distribution coefficient is adjusted according to the working status andcircumstances. Simulation results show that higher information efficiency, higher precision,fault-tolerance and stability can be obtained.
3. According to the essence of estimate and the intrinsic property of estimate optimality,the optimality of information fusion estimation methods in integrated navigation system isanalyzed. The optimality of Kalman filter in the case of colored noise, Kalman filter in thecase of the correlated noise, decentralized filter in the case of correlated sensor noises,federated filter in the case of correlated estimate, federated filter in the case of differentstructures, and federated filter in the case of different dimensions, are analyzed by theoreticalanalysis and experimental analysis with the optimal rule of linear minimum variance. Thenthe optimality of self-adaptive federated filter based on time series analysis in ideal conditionsand non-ideal conditions are analyzed, which proves that adaptive improvement does notaffect the optimality of the federated filter.
4. The method about how to apply the multi-model theory to integrated navigationsystem is researched. The redundant navigation system based on multi-model adaptiveestimation method is researched in the paper, and two ways of analytical redundancynavigation system are analyzed. The multi-model adaptive estimation fusion algorithm inDR/INS redundant integrated navigation system is proposed to guarantee the long time navigation of underwater vehicle. To solve the fusion estimation inaccuracy and long-timefilter divergence caused by model errors, an improved federated filter based on interactivemulti-model is proposed, in which federated filter structure is used to eliminate the correlatedestimate, and interactive multi-model is used instead of Kalman filter. The model error isrestrained by covering the range of the process noise covariance matrix and measurementnoise covariance matrix. And the anti-interference and stability can be obtained when theunderwater vehicle sails in long time.
引文
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