Pedestrian Positioning Method Based On MIMU Under Random Gaits

Foot-mounted passive sensor pedestrian positioning technology has attracted wide attention at home and abroad,and has great application value in the indoor environment of its field,large-scale supermarkets,and sudden natural disasters.At present,the research on the pedestrian-based passive sensor positioning system with the inertial sensor as the core has gradually become the hotspot.The inertial sensor based on foot-mounted passive sensor pedestrian positioning system has the advantages of small size,light weight,no radiation,and integration,and it can achieve full autonomous positioning.This has extremely important application value in environments where external satellite signals cannot be normally received,such as counter-terrorism attacks,firefighting and disaster relief.In the pedestrian-based passive sensor pedestrian positioning system,the sensor is fixedly connected to the pedestrian's foot,and the pedestrian's speed,position,and attitude information can be obtained by collecting the acceleration and angular velocity information of the pedestrian foot in real time,performing coordinate transformation and integral calculation.Hereinafter referred to as pose information).However,due to the manufacturing cost and the processing technology,the output of the inertial device contains errors,which will cause the pedestrian positioning information to contain errors and the errors diverge over time.Zero velocity update algorithm is an effective positioning error suppression algorithm.It uses the cyclical characteristics of pedestrian foot movements,that is,pedestrians will touch the ground for a short period of time(this time is called the zero velocity interval)for pedestrians to correct the positioning information.The existing zero velocity update algorithm has better error suppression effect when pedestrians walk at normal speed.However,the effect of zero velocity update is drastically reduced when pedestrians move fast or at variable speeds.In other words,the existing zero velocity update algorithm is insufficiently applicable.In order to solve the problem of the poor applicability of the existing zero velocity update algorithm,this paper proposes an adaptive zero-speed interval adjustment algorithm for nonsynchronous state and a positive and negative error suppression algorithm based on an adaptive zero-speed interval.The former improves the detection of pedestrian positioning systems.Zerospeed interval accuracy,which improves the degree of filter convergence in error correction algorithms.The use of these two algorithms to assist the existing zero-speed correction algorithm can achieve more accurate positioning of pedestrians during fast movements and variable speed movements,improve the applicability of the zero-speed correction algorithm,and improve the foot-trapped passive sensor pedestrian positioning system.However,in the zero velocity update process,the pedestrian heading error is unobservable,which can lead to the accumulation of pedestrian positioning errors over time in long navigation time positioning.In order to improve the observability of pedestrian heading errors and suppress the position error of pedestrians,this paper uses a dual passive sensor positioning system.In the dual passive sensor pedestrian positioning system,information fusion algorithm is the key to affect the positioning accuracy.The dual-passive sensor pedestrian positioning system used in this paper connects the two passive sensors to the pedestrian's left and right foot respectively,and uses the physical relationship between the feet during pedestrian movement to construct an equation-constrained model and solve the left The pose information of the right foot and the position information of both are simultaneously subjected to equality-constrained filtering,mutually correcting the mutual information of the two feet,improving the observability of the heading information,suppressing the divergence of the heading error,and ensuring the pedestrian positioning system.Reliability during positioning in long-haul navigation.Finally,using the Msi-G710 miniature passive sensor system of XSENS company in the Netherlands,the experiment was conducted to verify the correctness and reliability of the proposed method.During the test,the pedestrians were selected for different trajectories and movement speeds,and the applicability of the proposed method was analyzed and verified.The experimental results show that the algorithm can effectively reduce the accumulated error of positioning and improve the accuracy of pedestrian positioning.