【作者】 吕孝乐；

【导师】 赵国良；

【作者基本信息】 哈尔滨工程大学 ， 控制理论与控制工程， 2002， 硕士

【摘要】 随着导航技术和控制理论的发展，船舶组合导航系统已经成为当今最主要的船舶导航系统。船舶组合导航系统包括许多导航传感器，因此如何充分有效的处理来自多传感器的数据已成为船舶组合导航系统的主要问题。而多传感器的数据融合技术为此提供了强有力的手段。本文以DR/GPS/劳兰C船舶组合导航系统为研究对象，从数据融合的角度出发，为提高船舶组合导航系统的导航精度和容错能力提供了有效的解决方法。 本论文分为两大部分。第一大部分是讨论怎样消除随机误差对船舶组合导航系统的干扰，主要建立了DR/GPS/劳兰C船舶组合导航系统的数学模型，并用集中式卡尔曼滤波算法和联邦滤波算法对其进行了仿真，验证了算法的有效性。 第二大部分是船舶组合导航系统的故障检测。在这部分里，首先介绍了故障检测的有关理论，接着进行了仿真。最后，对模糊神经网络理论在船舶组合导航系统故障检测中的应用进行了研究。更多还原

【Abstract】 With the development of navigation technology and control theory, the integrated navigation system has already become the main navigation system at present. It is composed of many navigation sensors, so how to make the best of the data coming from the multi-sensors is the most important problem in the navigation system. The method of information fusion is one of the powerful means to solve this problem. In this paper, the DR/GPS/LoRan C integrated navigation system is studied in theory , and an effective way to solve this problem is given.This paper consists of two parts. In the first part, it discusses how to avoid the random disturbance in the integrated navigation system. The mathematical model of this system is established and the system is simulated with the help of Kalman filter and federal filter. The results of the simulation show that both Kalman filter and federal filter are effective.In the second part, fault diagnosis in the integrated navigation system is studied. At first, some theory of fault diagnosis is introduced. Then, some simulation is made. In the end, neural network theory is discussed and applied in the fault diagnosis.更多还原