水下航行器组合导航系统与信息融合技术研究
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摘要
水下航行器作为开发海洋的重要手段，具有活动范围广、体积小、隐蔽性好等优点，在民用和军事上均得到了广泛应用。随着水下航行器对导航精度要求的不断提高，高精度导航是其可靠、安全地完成水下导航任务的技术保障，而且面对水下复杂多变的工作环境，单一的导航方式在水下航行器应用中具有很大的局限性。因此，本文针对水下航行器的工作过程和实际应用需求，对水下航行器组合导航系统与信息融合技术展开深入研究。论文研究的主要工作有：
1、针对水下航行器在实际应用中无法完成自对准的问题，研究了基于SINS/GPS的水下航行器动基座对准技术。首先，基于欧拉平台误差角建立了捷联惯导系统在大方位失准角条件下的非线性误差模型；其次，为了克服对准中系统会受观测粗差和噪声统计特性不准确的影响，提出了自适应抗差CKF滤波算法；最后，通过仿真分析和实船试验，验证了该算法能够提高滤波的估计精度和收敛速度，增强滤波算法的稳定性和自适应能力，能够满足水下航行器动基座对准的要求。
2、针对传统标定方法在实际使用和维护方面的不便，研究了基于SINS/CNS的水下航行器陀螺误差在线标定技术。首先，基于四元数误差建立了陀螺误差在线标定模型；其次，为了解决系统维数较高会导致实时性变差的问题，通过对系统状态变量的可观测性分析，提出了模型预测滤波和递推滤波相结合的混合滤波算法；最后，通过仿真分析，验证了该算法的有效性和优越性。
3、针对GPS等基于无线电传播的导航设备无法在水下使用的局限性，研究了水下航行器SINS/DVL组合导航技术。首先，建立了SINS/DVL组合导航系统的数学模型，分析了不同校正方式对滤波的影响，并通过仿真验证了混合校正方式的优越性；其次，在水下航行器的实际导航工作中，为了解决系统量测噪声未知或时变、系统模型存在误差的问题，分别提出了简化Sage-Husa自适应Kalman滤波算法和估计方差阵自动加权Kalman滤波算法；最后，通过仿真分析和试验，验证了上述滤波算法对于提高滤波灵活性、抑制滤波发散起到了一定作用，提高了水下航行器SINS/DVL组合导航的精度。
4、针对长时间、远航程水下航行器的高精度导航需求和工作特点，研究了基于SINS/GPS水面校正的远程水下航行器组合导航技术。首先，建立了SINS/GPS组合导航系统的数学模型；其次，为了克服浪涌、阵风和机动变化等干扰因素对水下航行器水面校正过程的影响，以及解决GPS在高动态环境下可能会出现量测野值的问题，提出了具有抗野值功能的强跟踪自适应Kalman滤波算法；最后，通过仿真分析和试验，验证了该算法能够在实际应用中提高导航的定位精度。
5、为了实现多水下导航传感器信息的有效融合以及进一步提高水下导航精度，研究了基于SINS/DVL/MCP/TAN的水下航行器信息融合技术。首先，建立了相应组合导航系统的数学模型，基于PWCS理论和奇异值分解的可观测性分析，分别对SINS/DVL组合导航系统、SINS/DVL/MCP组合导航系统、SINS/DVL/MCP/TAN组合导航系统进行了可观测性分析，得到了最佳的组合方式，以提高滤波的估计能力；其次，水下航行器在实际应用中，其导航传感器可能会伴随有色噪声，而且信息分配系数的选取会影响联邦滤波器的性能，针对上述问题，提出了基于改进的Elman网络的自适应联邦H_∞滤波算法；最后，通过仿真分析，表明了该算法能够满足水下航行器的实际导航需求。
As an important means for exploring ocean, underwater vehicle is widely applied incivilian and military. With the continuous improvement of requirements for navigationaccuracy, high-precision navigation is technical support for underwater vehicle fulfillingunderwater navigation tasks reliably and safely, Meanwhile, face to the complex underwaterwork environment, single navigation method has serious limitations in the application ofunderwater vehicle. Therefore, in view of the work process and actual applicationrequirements for underwater vehicle, this paper is researched on AUV integrated navigationsystem and information fusion technology, the major research work is as follows:
1、In view of that underwater vehicle cannot quickly fulfill self-alignment, AUV movingbase initial alignment technology based on SINS/GPS is researched. First, based on Eulerplatform error angle, the nonlinear error model of strapdown inertial navigation system with alarge azimuth misalignment angle is established. Secondly, adaptive robust CKF algorithm isproposed to overcome that system will be affected by observation gross errors and inaccuratenoise statistical characteristics. Finally, According to simulation analysis and experimentalverification, adaptive robust CKF algorithm not only can improve the filter estimationaccuracy and convergence rate, but also can augment the stability and adaptive capacity, andwhich can meet the requirement of underwater vehicle moving base initial alignment.
2、In view of the inconvenience of actual use and maintenance for traditional calibrationmethod, underwater vehicle gyro error on-line calibration technology based on SINS/CNS isresearched. First, gyro error on-line calibration model based on quaternion error is established.Secondly, in order to solve the problem that high-dimension system will make real-timereduced, according to the observable degree analysis of system state variable, and the mixedfilter algorithm combined by model prediction filter and recursive filter is proposed. Finally,according to the simulation analysis, the feasibility and superiority is verified.
3、In view of the limitation that GPS and other navigation equipments communicating byradio cannot apply in water, AUV SINS/DVL integrated navigation technology is researched.First, SINS/DVL mathematical model is established, the affection of different correctionmethods on filter is analyzed, and the superiority of mixed correction method is verifiedaccording to the simulation. Secondly, in AUV actual navigation work, in order to solvesystem measurement noise may be unknown or time-varying and errors may exist in systemmodel, simplified Sage-Husa adaptive Kalman filter and estimation variance adaptiveweighting Kalman filter are proposed. Finally, according to the simulation analysis and experimental verification, the filter algorithm above can improve filter flexibility and restrictfilter divergence, and can on-line estimate the unknown or time-varying system measurementnoise and improve AUV SINS/DVL navigation accuracy.
4、In view of the high-accuracy navigation requirement and working characteristics,remote AUV integrated navigation technology based on SINS/GPS water correction processis researched. First, SINS/GPS mathematical model is established. Secondly, in order toovercome the affection of surge, gusts and motivational variation, and to solve the problemthat GPS in high dynamic circumstance may appear measurement wild value, trackingadaptive Kalman filter algorithm with fault-tolerant is proposed. Finally, according to thesimulation analysis and experimental verification, the algorithm can improve navigationaccuracy in actual application.
5、In order to fulfill the telling fusion of multi-sensor information and to further improveunderwater vehicle navigation accuracy, AUV information fusion technology based onSINS/DVL/MCP/TAN is researched. First, the corresponding integrated navigation systemmathematical model is established, based on PWCS and singular value decomposition,SINS/DVL integrated navigation system, SINS/DVL/MCP integrated navigation system, andSINS/DVL/MCP/TAN integrated navigation system are carried on observable analysis, andthen the best integrated method can be obtained to improve filter estimation capacity.Secondly, in AUV actual application, the measurement noise of navigation sensors may becolored noise, and that the determination of information distribution coefficient will affect theperformance of federal filter, in view of above problems, adaptive federal H_∞filteralgorithm based on developed Elman network is proposed. The simulation results show thatthe algorithm can meet AUV actual navigation requirement.
1、针对水下航行器在实际应用中无法完成自对准的问题，研究了基于SINS/GPS的水下航行器动基座对准技术。首先，基于欧拉平台误差角建立了捷联惯导系统在大方位失准角条件下的非线性误差模型；其次，为了克服对准中系统会受观测粗差和噪声统计特性不准确的影响，提出了自适应抗差CKF滤波算法；最后，通过仿真分析和实船试验，验证了该算法能够提高滤波的估计精度和收敛速度，增强滤波算法的稳定性和自适应能力，能够满足水下航行器动基座对准的要求。
2、针对传统标定方法在实际使用和维护方面的不便，研究了基于SINS/CNS的水下航行器陀螺误差在线标定技术。首先，基于四元数误差建立了陀螺误差在线标定模型；其次，为了解决系统维数较高会导致实时性变差的问题，通过对系统状态变量的可观测性分析，提出了模型预测滤波和递推滤波相结合的混合滤波算法；最后，通过仿真分析，验证了该算法的有效性和优越性。
3、针对GPS等基于无线电传播的导航设备无法在水下使用的局限性，研究了水下航行器SINS/DVL组合导航技术。首先，建立了SINS/DVL组合导航系统的数学模型，分析了不同校正方式对滤波的影响，并通过仿真验证了混合校正方式的优越性；其次，在水下航行器的实际导航工作中，为了解决系统量测噪声未知或时变、系统模型存在误差的问题，分别提出了简化Sage-Husa自适应Kalman滤波算法和估计方差阵自动加权Kalman滤波算法；最后，通过仿真分析和试验，验证了上述滤波算法对于提高滤波灵活性、抑制滤波发散起到了一定作用，提高了水下航行器SINS/DVL组合导航的精度。
4、针对长时间、远航程水下航行器的高精度导航需求和工作特点，研究了基于SINS/GPS水面校正的远程水下航行器组合导航技术。首先，建立了SINS/GPS组合导航系统的数学模型；其次，为了克服浪涌、阵风和机动变化等干扰因素对水下航行器水面校正过程的影响，以及解决GPS在高动态环境下可能会出现量测野值的问题，提出了具有抗野值功能的强跟踪自适应Kalman滤波算法；最后，通过仿真分析和试验，验证了该算法能够在实际应用中提高导航的定位精度。
5、为了实现多水下导航传感器信息的有效融合以及进一步提高水下导航精度，研究了基于SINS/DVL/MCP/TAN的水下航行器信息融合技术。首先，建立了相应组合导航系统的数学模型，基于PWCS理论和奇异值分解的可观测性分析，分别对SINS/DVL组合导航系统、SINS/DVL/MCP组合导航系统、SINS/DVL/MCP/TAN组合导航系统进行了可观测性分析，得到了最佳的组合方式，以提高滤波的估计能力；其次，水下航行器在实际应用中，其导航传感器可能会伴随有色噪声，而且信息分配系数的选取会影响联邦滤波器的性能，针对上述问题，提出了基于改进的Elman网络的自适应联邦H_∞滤波算法；最后，通过仿真分析，表明了该算法能够满足水下航行器的实际导航需求。
As an important means for exploring ocean, underwater vehicle is widely applied incivilian and military. With the continuous improvement of requirements for navigationaccuracy, high-precision navigation is technical support for underwater vehicle fulfillingunderwater navigation tasks reliably and safely, Meanwhile, face to the complex underwaterwork environment, single navigation method has serious limitations in the application ofunderwater vehicle. Therefore, in view of the work process and actual applicationrequirements for underwater vehicle, this paper is researched on AUV integrated navigationsystem and information fusion technology, the major research work is as follows:
1、In view of that underwater vehicle cannot quickly fulfill self-alignment, AUV movingbase initial alignment technology based on SINS/GPS is researched. First, based on Eulerplatform error angle, the nonlinear error model of strapdown inertial navigation system with alarge azimuth misalignment angle is established. Secondly, adaptive robust CKF algorithm isproposed to overcome that system will be affected by observation gross errors and inaccuratenoise statistical characteristics. Finally, According to simulation analysis and experimentalverification, adaptive robust CKF algorithm not only can improve the filter estimationaccuracy and convergence rate, but also can augment the stability and adaptive capacity, andwhich can meet the requirement of underwater vehicle moving base initial alignment.
2、In view of the inconvenience of actual use and maintenance for traditional calibrationmethod, underwater vehicle gyro error on-line calibration technology based on SINS/CNS isresearched. First, gyro error on-line calibration model based on quaternion error is established.Secondly, in order to solve the problem that high-dimension system will make real-timereduced, according to the observable degree analysis of system state variable, and the mixedfilter algorithm combined by model prediction filter and recursive filter is proposed. Finally,according to the simulation analysis, the feasibility and superiority is verified.
3、In view of the limitation that GPS and other navigation equipments communicating byradio cannot apply in water, AUV SINS/DVL integrated navigation technology is researched.First, SINS/DVL mathematical model is established, the affection of different correctionmethods on filter is analyzed, and the superiority of mixed correction method is verifiedaccording to the simulation. Secondly, in AUV actual navigation work, in order to solvesystem measurement noise may be unknown or time-varying and errors may exist in systemmodel, simplified Sage-Husa adaptive Kalman filter and estimation variance adaptiveweighting Kalman filter are proposed. Finally, according to the simulation analysis and experimental verification, the filter algorithm above can improve filter flexibility and restrictfilter divergence, and can on-line estimate the unknown or time-varying system measurementnoise and improve AUV SINS/DVL navigation accuracy.
4、In view of the high-accuracy navigation requirement and working characteristics,remote AUV integrated navigation technology based on SINS/GPS water correction processis researched. First, SINS/GPS mathematical model is established. Secondly, in order toovercome the affection of surge, gusts and motivational variation, and to solve the problemthat GPS in high dynamic circumstance may appear measurement wild value, trackingadaptive Kalman filter algorithm with fault-tolerant is proposed. Finally, according to thesimulation analysis and experimental verification, the algorithm can improve navigationaccuracy in actual application.
5、In order to fulfill the telling fusion of multi-sensor information and to further improveunderwater vehicle navigation accuracy, AUV information fusion technology based onSINS/DVL/MCP/TAN is researched. First, the corresponding integrated navigation systemmathematical model is established, based on PWCS and singular value decomposition,SINS/DVL integrated navigation system, SINS/DVL/MCP integrated navigation system, andSINS/DVL/MCP/TAN integrated navigation system are carried on observable analysis, andthen the best integrated method can be obtained to improve filter estimation capacity.Secondly, in AUV actual application, the measurement noise of navigation sensors may becolored noise, and that the determination of information distribution coefficient will affect theperformance of federal filter, in view of above problems, adaptive federal H_∞filteralgorithm based on developed Elman network is proposed. The simulation results show thatthe algorithm can meet AUV actual navigation requirement.
引文
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