Kalman Filtering Based Fault Tolerant Integrated INS/Radar Altimeter
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Navigation and guidance of a flight vehicle require that the altitude of the vehicle must be determined accurately. For this purpose different altimeter measurements can be integrated using Kalman filtering. In this monograph, the integrated navigation system, consisting of INS and radar altimeters, is presented. INS and the radar altimeter have different benefits and drawbacks. While having outstanding high frequency characteristics, the INS is a dead-reckoning system, at which the errors accumulate time by time. The radar altimeter, as a stand-alone system, gets timely updated measurements, ...
Navigation and guidance of a flight vehicle require that the altitude of the vehicle must be determined accurately. For this purpose different altimeter measurements can be integrated using Kalman filtering. In this monograph, the integrated navigation system, consisting of INS and radar altimeters, is presented. INS and the radar altimeter have different benefits and drawbacks. While having outstanding high frequency characteristics, the INS is a dead-reckoning system, at which the errors accumulate time by time. The radar altimeter, as a stand-alone system, gets timely updated measurements, but as it has an indolent principle of operation, it generates dynamical errors. The reason for integrating these two navigators is mainly to combine the best features, and eliminate the shortcomings of these devices. The integration is achieved by using an indirect Kalman filter. In the open loop system, INS is the main source of information, and radar altimeter provides discrete aiding data to support the estimations. The fault tolerant integrated INS/Radar altimeter based on proposed robust and adaptive Kalman filter algorithms is developed.
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