Pedestrian autonomous navigation calculation algorithm based on MEMS-IMU

Abstract

The invention discloses a pedestrian autonomous navigation calculation algorithm based on an MEMS-IMU. Two IMU systems are simultaneously and fixedly connected with the two feet of the user of a pedestrian navigation system; the two systems respectively perform a strapdown inertial navigation calculation algorithm and a zero-speed correcting algorithm on the basis of Kalman filtering, and then the positioning information of the two feet is fused; when the calculation distance between two feet exceeds the largest step size gamma between the two feet, inequality constraint is performed on navigation results of two IMUs by adopting a state constraint Kalman filtering algorithm, so that vague human physiological property problem is converted into a rigid mathematical problem, the optimal estimation of navigation results is achieved, and pedestrian navigational positioning function with higher accuracy is achieved.

Description

Technical field: [0001] The present invention relates to a navigation solution algorithm, in particular to a pedestrian autonomous navigation solution algorithm based on dual MEMS-IMU (micro mechanical system-inertial measurement unit). Background technique: [0002] In recent years, with the improvement of the precision of MEMS inertial devices at home and abroad, it is possible to use the strapdown inertial navigation system calculation algorithm to carry out pedestrian dead reckoning, especially the use of strapdown inertial navigation calculation algorithm can provide more complete navigation information . But even so, if it works for a long time, the MEMS inertial device error will still diverge seriously. The pedestrian dead reckoning results obtained by the strapdown inertial navigation solution algorithm verify that if the MEMS inertial device error cannot be effectively compensated during navigation, the position error It will diverge with the trend of the cube of ...

AI Technical Summary

Problems solved by technology

Most of the error compensation algorithms based on zero-speed correction have defects such as inaccurate zero-speed detection, lagging detection results, and short zero-speed correction time. Although the navigation accuracy of pedestrian autonomous navigation systems can be improved within a certain range, the navigation positioning error is still large. , and only for a short time

All in all, the accuracy of existing navigation calculation algorithms is poor, and it is difficult to meet the precise and reliable requirements of pedestrian autonomous navigation.

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