Integrated Navigation System, Information Fusion And Fault Detection Theory

The boom of modern naviation technology urgently requires its navigation system to be more accurate and more reliable. It is unpractical to meet both demands by any kind of navigation equipment separately. When the classical Centralized Kalman Filter (CKF) is used in this kind of integration, there will be two disadvantages: firstly, there exists real time computation difficulty. Secondly, the fault tolerance capability is poor. Once one of the subsystems breaks down, all the other subsystems are affected. In this thesis, on the basis of Federated Kalman filtering theory and aiming at a certain type of airplane equipped with many navigation equipments such as SINS, GPS,etc., the integrated navigation system with the fault tolerance property is designed. The following important work has been done: (1)Some special problems of rate-bias laser gyro were analysed. The problems include modulation and demodulation of the output and algorithm of the attitude updates; (2)The integrated navigation system with the fault tolerance property which equipped with many navigation equipments as SINS, GPS, DVS, ADS, MG, VG is designed,and compared with that of CKF via simulations; (3)The theories and methods of system level fault detection apply to Federated Filtering is investigated; (4)The problem about using the fused information of SINS based on rate-bias laser gyroscope/dynamical tune gyroscope to realize the component level hard fault interactions detection through a Back-Propagation neural network is discussed. The methodology and innovation in this paper is: (1)The problems which include modulation and demodulation of the rate biased laser gyro's output, algorithm of attitude updates,etc.are analysed. (2)The component level fault interactions detection of SINS based on rate-bias laser gyro/dynamical tune gyroscope by using artificial neural network is investigated.