Initial Alignment Of Inertial Strapdown Navigation System Using H_∞ Filtering

Initial alignment is one of the key technology of Inertial Navigation System. It directly influence the navigation performance of navigation system . Because some random factors exist in the system, there are some difference between the precision of Initial alignment and alignment time . Therefore, higher precision, more time. The system error is mainly determined by sensor error and initial alignment error by analyzing the error transfer characteristic of the SINS system. After compensating the sensor error, the precision of the whole system almost remains the Initial alignment process. It should include of gyroscope and speedmeter to compensate the error. Initial alignment is to put on some speed of control angel in order to transferring the maths platform to expected location. It can be controlled by error equation. In the platform system, it used to adopt the modern control theory method.At present , the application of Kalman filtering technology has provided an efficient method for the quick alignment of SINS system. Adopting the Kalman filtering aimed by itself means using it to give the best estimate about the platform error angle. Using the correction system to the correction between the platform coordinate and navigation coordinate. The artificial result shows that the application Kalman filtering for SINS system can bring a good result but Kalman filtering is done in the ideal situation. In other words, it requires the precision of the active model and the noise is the white noise which statistical characteristic can be shown. We could not meet the needs during the actual application, so the application of Kalman filtering has to be limiter by some premise condition. Moreover, Kalmanfiltering does not have robust characteristic to the undetermined factors between model and noise. To solve the problem, the author introduces the H_∞ filtering to the initial alignment and designs the H_∞filtering which owns robust characteristic.