Movement classification-based pedestrian self-positioning method

Abstract

The invention discloses a movement classification-based pedestrian self-positioning method. The method comprises the following steps: 1, classifying data output by a wearable IMU on a pedestrian, and recognizing IMU placing positions of feet, a waist and a chest in an adaptive manner; 2, determining thresholds for the movement classification division through analyzing data output by the wearable IMU to classify movement such as staying, walking and running; 3, performing recognition capture at transient moments in the movement state of the pedestrian; 4, acquiring the pedestrian attitude, speed, position information through the navigation solution of strap-down inertial navigation; 5, realizing the adaptive filtering design combined with the IMU position reorganization, the movement classification result and the transient moment detection result; 6, updating a navigation result in the pedestrian movement process. Through the adoption of the method, the movement data classification problem is solved; through the movement classification, different movement types can correspond to different size-length models, so that the positioning accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of navigation and positioning, in particular to a pedestrian autonomous positioning method based on motion classification. Background technique [0002] Pedestrian autonomous navigation system (including MEMS three-axis magnetometer, MEMS three-axis accelerometer, MEMS three-axis gyroscope) is mainly used for personal autonomous navigation and real-time positioning under known or unknown conditions, assisting in the completion of various types of emergency rescue tasks . When emergency accidents such as fires and earthquakes occur, there may be situations at the scene of the accident that are not conducive to rescue, such as reduced visibility and inherent environmental changes. Rescuers cannot quickly and accurately identify their own positions. At this time, the positioning information provided by the pedestrian navigation system can provide effective technical support for rescuers. [0003] Most of the ...

AI Technical Summary

Problems solved by technology

Although using kinematics approximation to estimate the step length can avoid the position error caused by the distance obtained by the double integration of the acceleration value, but this empirical method cannot recognize the gait changes of different people, so when using a different method from the past Will fail when moving, and will fail completely in abnormal environments, such as crowded environments or going up and down hills

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