GPS/INS integrated navigation method based on unscented Kalman filtering

The invention relates to a GPS/INS integrated navigation method based on unscented Kalman filtering. The method is mainly characterized in that the method comprises the following steps that INS data and corresponding GPS data are combined together, and an unscented Kalman filtering method is adopted to build a GPS/INS integrated navigation model to obtain the online optimal value of a GPS; the INS data are used as training data and are combined with the online optimal value of the GPS as a training target to build an SVM regression model, and the SVM regression model is used for predicting the off-line navigation data of the GPS. According to the method, the precision of the GPS is usually combined with the reliability of an inertial navigation system to achieve the information fusion of the filtering, the GPS and an INS, and when the GPS and the INS are used together, a precise filtering result can be obtained; an SVM is adopted to train INS data obtained when GPS signals are lost, the parameters of a kernel function and a penalty function in an SVM algorithm are optimized through a simulated annealing algorithm, and the precision of the off-line GPS is kept close to that of the online GPS.