Dual Mimu Pedestrian Navigation Algorithm Based On Multiple Conditional Constraints

For the characteristics of small size,low power consumption and low price,independent navigation can be achieved by MIMU-based strapdown pedestrian inertial navigation system without external signals.It is suitable for indoor environments without electromagnetic positioning signals,and has gradually become a research hotspot in the field of indoor navigation.Due to the inherent characteristics of the inertial device,the error of the pedestrian inertial navigation system accumulates over time,making it difficult to achieve high-precision positioning for a long time.In order to reduce the cumulative error of pedestrian inertial navigation system and improve navigation accuracy,this paper establishes a constraint equation based on the motion characteristics of pedestrian bipeds,and proposes a multi-condition constrained pedestrian navigation algorithm to improve the accuracy of pedestrian positioning.The main work of the thesis is as follows:(1)Dual-MIMU navigation systemThere is heading drift in single MIMU pedestrian inertial navigation system due to the low observational effect of the gyroscopic gyro.In view of the shortcomings of the single-foot pedestrian inertial navigation system,this paper adopts the dual MIMU navigation scheme.The MIMU is fixed to each of the two feet.At the same time,the inertial data of pedestrian movement is collected,and the pedestrian inertial navigation algorithm is designed by using pedestrian movement characteristics.(2)Zero-velocity detection and zero-velocity correction algorithmA three-condition zero-velocity detection method and a zero-velocity correction algorithm based on Kalman filtering are used.The zero-velocity correction technology is the simplest and most effective error compensation technology in the pedestrian inertial navigation system.The Kalman filter method is used to compensate the zero-speed error,and the positioning accuracy is effectively improved.(3)Constraint algorithmBased on the dual-MIMU navigation scheme,the maximum step constraint algorithm for bipeds and the maximum distance constraint algorithm between bipeds are proposed.According to the relationship between the foot and the foot of a single foot,the maximum step constraint algorithm for single foot is proposed.For the same foot,the distance between the two front and back points does not exceed a certain maximum value during one-step movement.This maximum value is the maximum step size of one foot.The optimal solution of the Kalman filter satisfying this constraint has higher navigation accuracy.(4)Multi-condition constraint algorithm and experimental verificationThe multi-conditional constraint algorithm combining the zero-speed correction,the biped constraint algorithm and the single-step maximum step constraint algorithm is more in line with the pedestrian motion characteristics than the single constraint algorithm.The same set of data is used to solve the problem of multi-conditional constraint algorithm by using zero-speed correction,biped maximum step constraint algorithm,maximum distance constraint algorithm between bipedal trajectories,single-step maximum step constraint algorithm and multi-condition constraint algorithm.The calculated position accuracy is higher.Based on the dual-MIMU navigation scheme,this paper proposes a multi-condition constrained pedestrian navigation algorithm.The validity and feasibility of the pedestrian navigation algorithm are verified by experiments,which provides a way of thinking for the research of pedestrian inertial navigation algorithm.