船舶动力定位系统多传感器信息融合方法研究
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摘要
随着动力定位技术和测控理论的发展，现代船舶动力定位系统配备了船舶位置、姿态及环境测量等多种传感器，构成一个多传感器测量系统。信息融合技术是解决多源信息综合处理问题的强有力手段，通过多传感器信息的最优融合，能够有效地提高动力定位测量系统的精度和可靠性。本论文旨在研究信息融合理论在动力定位系统中的应用。
在船舶动力定位多传感器融合系统中，船舶运动模型、传感器测量模型及滤波算法是船舶运动状态最优滤波的基础，直接影响着滤波精度、滤波算法的稳定性及实用性，传感器的故障检测与容错是多传感器融合系统可靠性和有效性的有力保证，融合算法决定了融合系统的精度，因此，本论文从上述几个方面对船舶动力定位多传感器信息融合的方法进行研究，论文的主要工作有：
分析了动力定位船的运动特性和动力定位系统各位置参考系统的测量机理，提出动力定位船的连续白噪声加速度运动模型，并在北东坐标系下建立船舶位置参考系统的线性测量模型。
研究了传感器突变型故障检测与容错算法，根据传感器的不同故障状态设定多个阈值，使得该算法同时检测传感器的突变型故障、测量信号冻结故障和测量野值。针对动力定位系统利用表决或中位数法检测传感器漂移性故障的局限性，利用多传感器的融合信息递推子系统的滤波残差，改进残差故障检测法，建立了基于多传感器信息融合的传感器渐变型故障检测与容错算法。
对于位置参考系统测量噪声统计特性可能存在的不准确性问题，提出一种自适应平方根容积卡尔曼滤波(Square-Root Cubature Kalman Filter, SRCKF)算法，根据新息协方差匹配原理计算自适应系数，实时地调整测量噪声协方差矩阵。针对动力定位船系统模型可能存在的不确定性问题及强跟踪滤波器的理论局限性，推导出强跟踪滤波器中渐消因子的等价计算方法，将SRCKF和自适应SRCKF与强跟踪滤波的理论框架相结合，构成强跟踪SRCKF和强跟踪自适应SRCKF两种算法。
针对动力定位系统利用时间配准技术处理异步信息存在的问题，将不同尺度上的测量模型及测量值利用小波分解统一变换到某一尺度上，然后在该尺度上进行同步多传感器的融合，实现异步多传感器多尺度最优融合估计；将系统最细尺度上的状态估计信息通过小波分解反馈给其他各尺度，再把各尺度上的状态估计结果向最细尺度进行小波重构，最后在最细尺度上进行同步信息的融合，实现异步多传感器最优分布式融合估计。
根据冗余动力定位系统的实际需求，设计同步、异步位置参考系统融合结构及同步姿态测量系统的融合结构，由此构成船舶动力定位系统多传感器信息融合的体系，利用本单位研制的船舶半实物仿真系统，对所建动力定位船运动模型、传感器测量模型、同步位置参考系统及同步姿态测量系统的融合结构与相应的算法进行仿真验证。
With the development of dynamic positioning (DP) technology and measurement andcontrol theory, the modern DP system equips with the position, attitude and environmentalsensors which form a multi-sensor measurement system. Information fusion technologyprovides all effective way to multi-source information processing problem. The accuracy andreliability of the measurement system of DP can be effectively improved by using themulti-sensor information fusion technology. This paper studies the application of informationfusion theory in the domain of dynamic positioning system.
For the multi-sensor fusion system of DP, ship motion model, sensor measurement modeland filtering algorithm are the basis of the optimal filtering of ship motion state. They directlyaffect the stability and accuracy of filter. The sensor fault detection and fault tolerance are theimportant measures to ensure the reliability and validity of multi-sensor fusion. The fusionmethod determines the accuracy of the fusion system. Therefore, this paper focuses onresearching deeply into the theory of the above five aspects of multi-sensor data fusion of DP.The main works are as follows:
The maneuvering characteristics of DP vessels are researched, and a continuous whitenoise acceleration motion model of DP ship is built. The measurement mechanisms ofposition reference systems (PRS) of DP system are studied, and the linear measurementmodels of position reference systems in the North-East coordinate frame are proposed.
The sensor mutant fault detection algorithm is studied. According to the different faultconditions some thresholds are set. This makes the sensor mutant fault algorithm to detect thesensor mutant failures, freezing signals and wild points. To overcome the limitation of sensordrift fault detection by voting or median method, based on multi-sensor information fusion asensor drift fault detection algorithm is proposed. By the reconstruction of filter residual withthe fusion information of multi-sensor, the sensor fault detection algorithm based on residualis improved effectively to detect sensor drift fault.
To overcome the effects of inaccuracies of measurement noise statistical characteristics,based on the innovation covariance matching principle an adaptive square-root cubatureKalman filter (SRCKF) algorithm is built. The method calculates the adaptive coefficients toreal-time adjustments the measurement noise covariance matrices. For the uncertainty ofsystem model and the theory limitations of the strong tracking filter (STF), the equivalentcalculating method of fading factor of STF is built, and the strong tracking SRCKF and strong tracking adaptive SRCKF algorithms are proposed by combining the SRCKF and adaptiveSRCKF with STF separately.
For the problem of processing asynchronous information by time registration method,two asynchronous multi-sensor information fusion algorithms are proposed based on themultiscale estimation theory. Using wavelet decomposition, the measurement models andmeasurements on different scales are transformed to one scale, and then asynchronousmulti-sensor information multiscale optimal fusion estimation is achieved by the synchronousmulti-sensor fusion on the specified scale. The state estimation information on the finest scaleis feedback to other scales by wavelet decomposing. With wavelet reconstruction, the stateestimations on other scales are transformed to the finest scale, and the asynchronousmulti-sensor information optimal distributed fusion estimation is realized by the synchronousinformation fusion on the finest scale.
According to the actual needs of the redundant dynamic positioning system, thestructures of synchronous and asynchronous position reference systems and synchronousattitude measurement system are designed. The proposed fusion structures form themulti-sensor information fusion system of DP. With the vessel semi-physical simulationsystem, the validities of the motion model of DP ship, sensor measurement models, the fusionconfigurations of synchronous PRS and synchronous heading measurement system areverified by the simulations.
在船舶动力定位多传感器融合系统中，船舶运动模型、传感器测量模型及滤波算法是船舶运动状态最优滤波的基础，直接影响着滤波精度、滤波算法的稳定性及实用性，传感器的故障检测与容错是多传感器融合系统可靠性和有效性的有力保证，融合算法决定了融合系统的精度，因此，本论文从上述几个方面对船舶动力定位多传感器信息融合的方法进行研究，论文的主要工作有：
分析了动力定位船的运动特性和动力定位系统各位置参考系统的测量机理，提出动力定位船的连续白噪声加速度运动模型，并在北东坐标系下建立船舶位置参考系统的线性测量模型。
研究了传感器突变型故障检测与容错算法，根据传感器的不同故障状态设定多个阈值，使得该算法同时检测传感器的突变型故障、测量信号冻结故障和测量野值。针对动力定位系统利用表决或中位数法检测传感器漂移性故障的局限性，利用多传感器的融合信息递推子系统的滤波残差，改进残差故障检测法，建立了基于多传感器信息融合的传感器渐变型故障检测与容错算法。
对于位置参考系统测量噪声统计特性可能存在的不准确性问题，提出一种自适应平方根容积卡尔曼滤波(Square-Root Cubature Kalman Filter, SRCKF)算法，根据新息协方差匹配原理计算自适应系数，实时地调整测量噪声协方差矩阵。针对动力定位船系统模型可能存在的不确定性问题及强跟踪滤波器的理论局限性，推导出强跟踪滤波器中渐消因子的等价计算方法，将SRCKF和自适应SRCKF与强跟踪滤波的理论框架相结合，构成强跟踪SRCKF和强跟踪自适应SRCKF两种算法。
针对动力定位系统利用时间配准技术处理异步信息存在的问题，将不同尺度上的测量模型及测量值利用小波分解统一变换到某一尺度上，然后在该尺度上进行同步多传感器的融合，实现异步多传感器多尺度最优融合估计；将系统最细尺度上的状态估计信息通过小波分解反馈给其他各尺度，再把各尺度上的状态估计结果向最细尺度进行小波重构，最后在最细尺度上进行同步信息的融合，实现异步多传感器最优分布式融合估计。
根据冗余动力定位系统的实际需求，设计同步、异步位置参考系统融合结构及同步姿态测量系统的融合结构，由此构成船舶动力定位系统多传感器信息融合的体系，利用本单位研制的船舶半实物仿真系统，对所建动力定位船运动模型、传感器测量模型、同步位置参考系统及同步姿态测量系统的融合结构与相应的算法进行仿真验证。
With the development of dynamic positioning (DP) technology and measurement andcontrol theory, the modern DP system equips with the position, attitude and environmentalsensors which form a multi-sensor measurement system. Information fusion technologyprovides all effective way to multi-source information processing problem. The accuracy andreliability of the measurement system of DP can be effectively improved by using themulti-sensor information fusion technology. This paper studies the application of informationfusion theory in the domain of dynamic positioning system.
For the multi-sensor fusion system of DP, ship motion model, sensor measurement modeland filtering algorithm are the basis of the optimal filtering of ship motion state. They directlyaffect the stability and accuracy of filter. The sensor fault detection and fault tolerance are theimportant measures to ensure the reliability and validity of multi-sensor fusion. The fusionmethod determines the accuracy of the fusion system. Therefore, this paper focuses onresearching deeply into the theory of the above five aspects of multi-sensor data fusion of DP.The main works are as follows:
The maneuvering characteristics of DP vessels are researched, and a continuous whitenoise acceleration motion model of DP ship is built. The measurement mechanisms ofposition reference systems (PRS) of DP system are studied, and the linear measurementmodels of position reference systems in the North-East coordinate frame are proposed.
The sensor mutant fault detection algorithm is studied. According to the different faultconditions some thresholds are set. This makes the sensor mutant fault algorithm to detect thesensor mutant failures, freezing signals and wild points. To overcome the limitation of sensordrift fault detection by voting or median method, based on multi-sensor information fusion asensor drift fault detection algorithm is proposed. By the reconstruction of filter residual withthe fusion information of multi-sensor, the sensor fault detection algorithm based on residualis improved effectively to detect sensor drift fault.
To overcome the effects of inaccuracies of measurement noise statistical characteristics,based on the innovation covariance matching principle an adaptive square-root cubatureKalman filter (SRCKF) algorithm is built. The method calculates the adaptive coefficients toreal-time adjustments the measurement noise covariance matrices. For the uncertainty ofsystem model and the theory limitations of the strong tracking filter (STF), the equivalentcalculating method of fading factor of STF is built, and the strong tracking SRCKF and strong tracking adaptive SRCKF algorithms are proposed by combining the SRCKF and adaptiveSRCKF with STF separately.
For the problem of processing asynchronous information by time registration method,two asynchronous multi-sensor information fusion algorithms are proposed based on themultiscale estimation theory. Using wavelet decomposition, the measurement models andmeasurements on different scales are transformed to one scale, and then asynchronousmulti-sensor information multiscale optimal fusion estimation is achieved by the synchronousmulti-sensor fusion on the specified scale. The state estimation information on the finest scaleis feedback to other scales by wavelet decomposing. With wavelet reconstruction, the stateestimations on other scales are transformed to the finest scale, and the asynchronousmulti-sensor information optimal distributed fusion estimation is realized by the synchronousinformation fusion on the finest scale.
According to the actual needs of the redundant dynamic positioning system, thestructures of synchronous and asynchronous position reference systems and synchronousattitude measurement system are designed. The proposed fusion structures form themulti-sensor information fusion system of DP. With the vessel semi-physical simulationsystem, the validities of the motion model of DP ship, sensor measurement models, the fusionconfigurations of synchronous PRS and synchronous heading measurement system areverified by the simulations.
引文
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