| It is an effective way to increase the cost performance ratio by integrating several kinds of navigation systems. This thesis designed an information fusion algorithm of SINS/GPS/EC integrated navigation system with its implementation. It highly improved the precision of the system.First, it pivoted on the design and analysis of SINS subsystem. The experimental research on typical MIMU sensors was made. Based on time series analysis, ARMA model identification and Kalman filter design of ADIS16350, a miniature gyroscope, has been presented to reduce the output noise, which served as an effective way to improve system accuracy. By comparing calculation precision and resolving time of several algorithms, engineering applied quaternion algorithm of strapdown navigation system has been chosen. After analyzing the error sources of strapdown inertial navigation system, systemic precision is estimated in advance based on the performance of employed sensors.Second, the paper studied filter design of SINS/GPS/EC integrated navigation system. Based on traditional information fusion of velocity and position, two sub-filters about velocity and position of GPS has been designed to integrate the signal of SINS, respectively, which effectively eliminated the influence of velocity jump of GPS. The two filters together with the filter of SINS/EC composed a federal Kalman filter. Finally, emulation has showed that a high fault-tolerant accuracy can get from this combination, and it can work with considerable precision in a long time even when the GPS signal has been lost.Ultimately, the overall hardware and software design of given integrated system has been put forward. In the process of debugging and testing of the system, it works stably. Based on static test of real SINS and integrated system, the result shows the effectivity of the algorithm adopted in this paper.
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