Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
Title Indoor Position Detection Algorithm Based on Multiple Magnetic Field Map Matching and Importance Weighting Method
Authors 김용훈(Yong Hun Kim) ; 김응주(Eung Ju Kim) ; 최민준(Min Jun Choi) ; 송진우(Jin Woo Song)
DOI http://doi.org/10.5370/KIEE.2019.68.3.471
Page pp.471-479
ISSN 1975-8359
Keywords Indoor navigation ; Map based navigation ; Multiple magnetic sensors ; Importance data weighting
Abstract This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.