Pedestrian positioning correction method based on distance approximation discrimination Bluetooth

Abstract

The invention relates to the field of indoor positioning, and discloses a pedestrian positioning correction method based on distance approximation discrimination Bluetooth. The method comprises the steps of: building a Bluetooth node network; performing parameter initialization configuration on a walker dead reckoning system; obtaining an equipment number and signal intensity of each observable Bluetooth node; performing gait recognition according to the accelerometer data; respectively comparing the signal intensity values of the observable Bluetooth nodes with a signal intensity identification threshold value; acquiring the positions of all observable Bluetooth nodes entering the proximity range of a mobile terminal according to the equipment number; sorting the distances from all the observable Bluetooth nodes entering the proximity range of the mobile terminal to the mobile terminal; performing observable Bluetooth distance approximation judgment; updating the parameters; performing proximity correction; and determining whether to continue positioning. According to the method, the problems that in the prior art, a signal intensity threshold method is large in correction error and has track bounce are solved, and the PDR correction precision and reliability are improved.

Description

technical field [0001] The invention relates to the technical field of indoor positioning, in particular to a pedestrian positioning correction method based on distance approach discrimination Bluetooth. Background technique [0002] At present, in view of the serious cumulative error problem in Pedestrian Dead Reckoning (PDR), many research teams have set up landmark positions in combination with special areas of indoor environments or specific behaviors of users in a certain place to correct the PDR process. The cumulative error problem in . In 2012, Wang et al. proposed UnLoc, which uses WiFi fingerprints at specific locations and sensor data at different locations as landmarks, and UnLoc's landmarks are automatically added to the system; in Shen's 2013 article, indoor elevators, escalators and Areas that cause special changes in sensors such as corners are used as virtual landmarks, through which the cumulative error in the PDR process is eliminated; in 2015, Chen et al...

AI Technical Summary

Problems solved by technology

However, the Bluetooth proximity discrimination method based on signal strength faces the difficulty of selecting the discrimination threshold in Bluetooth proximity discrimination.

When the threshold value is set too high, the correction range is reduced, and the possibility of users entering the correction area is reduced. There is a problem that the correction point is not recognized and the correction is missed.

When the threshold is set too low, the correction range is enlarged, and there are problems such as premature correction of the user position, large correction errors, obvious jumps of the user trajectory during correction, and stagnation of the user trajectory within a large correction range.

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