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Cubature kalman filter is prone to filtering divergence if the system model is inaccurate or measuring abnormal. In order to solve this problem, the adaptive cubature kalman filter algorithm was proposed in this paper, it constructed a group of noise statistic estimators to estimate the statistical characteristic of the noise in real time; and when the measurement anomaly, it adopted correction function to adjust the filtering process, and thus the estimation accuracy and the ability to restrain the filtering divergence can be improved effectively ; On the basis of centralized filter structure and federal filter structure, this paper designed a kinds of hybrid composite filter structure about multi-sensor system based on adaptive cubature kalman filter algorithm , and gave the method that fused the local filtering information of each sensor's to get the global filtering information; In the application background of positioning and navigation for vehicle to make simulation tests, and the results show the effectiveness of the proposed method.

Research Multi-Sensor Data Fusion Algorithm based on the adaptive cubature kalman filter