Pedestrian indoor positioning method fusing PDR and priori map

Abstract

The invention discloses a pedestrian indoor positioning method fusing a PDR and a prior map. The method comprises the steps: firstly respectively obtaining IMU data of an indoor map and a pedestrian,performing the LSD feature extraction of the obtained indoor map, and converting map information into a matrix with wall information; carrying out PDR processing on the obtained pedestrian IMU data toobtain an original pedestrian indoor track, and aligning the original pedestrian indoor track with a map after being processed; judging a'through-wall 'phenomenon by utilizing map information and theprocessed track information to obtain through-wall points and coordinates of the through-wall points; and finally, obtaining an optimal trajectory coordinate by adopting a particle filter algorithm,and updating a positioning result to obtain an optimal pedestrian indoor trajectory. According to the method, the positioning error caused by PDR integral characteristics is corrected, the positioningprecision is improved, and a better positioning effect is obtained.

Description

technical field [0001] The invention belongs to the technical field of positioning, and in particular relates to an indoor positioning method for pedestrians. Background technique [0002] The location service is divided into indoor and outdoor, and the global positioning system is used to assist in positioning outdoors. But in the indoor environment, due to the complex structure of the wall and other reasons, it is impossible to receive satellite signals. The PDR positioning method is passive and does not require external assistance, and the indoor positioning of pedestrians can be completed only by the IMU, which has become a common method for indoor positioning of pedestrians. However, PDR positioning will generate positioning errors. Although the inertial component IMU can be used to collect pedestrian gait data, and then perform gait detection to judge the moment when the pedestrian is still, and use the speed at this moment as the observation of the Kalman filter. Th...

AI Technical Summary

Problems solved by technology

However, PDR positioning will generate positioning errors. Although the inertial component IMU can be used to collect pedestrian gait data, and then perform gait detection to judge the moment when the pedestrian is still, and use the speed at this moment as the observation of the Kalman filter. Then correct the positioning error

However, since the method is based on double integration of acceleration, positioning errors will accumulate over time

Although the ZUPT and ZARU methods can be used to correct the error, it still cannot make the positioning result reach an optimal state.

At the same time, because the gait detection method may not be accurate enough, the positioning error will still exist.

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