WuYaqin, YangShuo, ShiLanlan. Research on indoor positioning algorithm based on location fingerprint and PDR[J]. Journal of Mining Science and Technology, 2019, 4(5): 448-454.
Citation:
WuYaqin, YangShuo, ShiLanlan. Research on indoor positioning algorithm based on location fingerprint and PDR[J]. Journal of Mining Science and Technology, 2019, 4(5): 448-454.
WuYaqin, YangShuo, ShiLanlan. Research on indoor positioning algorithm based on location fingerprint and PDR[J]. Journal of Mining Science and Technology, 2019, 4(5): 448-454.
Citation:
WuYaqin, YangShuo, ShiLanlan. Research on indoor positioning algorithm based on location fingerprint and PDR[J]. Journal of Mining Science and Technology, 2019, 4(5): 448-454.
To improve the indoor positioning accuracy, the methods of position fingerprint and pedestriandeadreckoning(PDR)areusedtostudytheindoorpositioningalgorithm.Forpositionfingerprintalgorithm,thefingerprintdatabaseisoptimizedthroughtheofflinedatatrainingphase,andthe optimizationofthenearestneighboralgorithmiscarriedoutbylimitingtheregionweightedvalue K throughtheonlinereal-timematchingphase.ForPDRalgorithm,theself-adaptationpeakdetectionalgorithmusedforstepfrequencydetectionisproposed.Theimprovednonlinearmodelisusedforstep sizeestimation.Moreover,Thegyroscope’sinformationarefusedtomagnetometer’sinformationinthe heading estimation.Finally, the unscented Kalman filter is used to fuse the position fingerprint algorithmandPDRmethod,whichimprovesthepositioningaccuracyandthepracticabilityofthefusion algorithmisverifiedbythepositioningsystem.
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