A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model

Lu, Yi; D, Wei; Lai, Qifeng; Li, Wen; Yuan, Hong

doi:10.3390/s16122030

Cited by 14 publications

(11 citation statements)

References 19 publications

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“…HMM has been used for map matching in related works . According to the statement in the related work, the output sequences of characteristic contexts satisfy the Markov property. This paper uses HMM to match the location‐related activities with the 2D road map.…”

Section: Traffic Mode Detection and Context‐based Map Matching For Oumentioning

confidence: 99%

“…Compared with the point‐to‐point map matching, the sequence‐to‐sequence map matching has a higher possibility of correcting the positioning error. Lu et al proposed a context‐recognition‐aided PDR localization model to calibrate PDR. The context is detected by employing particular human actions (turning left and right), and it is matched to the context pre‐stored offline in the database to obtain the pedestrian's location.…”

Section: Introductionmentioning

confidence: 99%

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Integration of positioning and activity context information for lifelog in urban city area

Kamiya

et al. 2019

NAVIGATION

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Smartphone‐based Lifelog (automatically annotating the users' daily experience from multisensory streams on smartphones) is in great need. Accurate positioning under any situation is one of the most significant techniques for a desirable Lifelog. This paper proposes to detect location‐related activities and use the activity information to improve positioning accuracy. In the proposed system, a human activity recognition module is developed to extract location‐related activities from multisensory streams of smartphones. After that, the proposed system integrates activity information with PDR‐based positioning results in a context‐based map‐matching framework. The developed system can be used for both outdoor and indoor scenarios. Moreover, the developed indoor positioning method is used to determine the positions of calibration points automatically in an auto‐calibration Wi‐Fi positioning system. The proposed methods achieve 3.1‐m accuracy in outdoor and average 2.2‐m accuracy in indoor situations.

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Section: Traffic Mode Detection and Context‐based Map Matching For Oumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration of positioning and activity context information for lifelog in urban city area

Kamiya

et al. 2019

NAVIGATION

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show abstract

“…The heading angle is the most important angle information in the attitude angle information. The change of heading angle information was directly used in [ 12 , 20 ] to detect pedestrian-related walking status. However, during the experiment, the sensor was fixed on the waist of the experimenter, and the heading angle information could not occur due to large fluctuations during the straight walking phase.…”

Section: Feature Point Mapmentioning

confidence: 99%

Research on PF-SLAM Indoor Pedestrian Localization Algorithm Based on Feature Point Map

et al. 2018

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Recently, the map matching-assisted positioning method based on micro-electromechanical systems (MEMS) inertial devices has become a research hotspot for indoor pedestrian positioning; however, these are based on existing indoor electronic maps. In this paper, without prior knowledge of the map and through building an indoor main path feature point map combined with the simultaneous localization and map building (SLAM) particle filter (PF-SLAM) algorithm idea, a PF-SLAM indoor pedestrian location algorithm based on a feature point map was proposed through the inertial measurement unit to improve indoor pedestrian positioning accuracy. Aiming at the problem of inaccurate heading angle estimation in the pedestrian dead reckoning (PDR) algorithm, a turn-straight-state threshold detection method was proposed that corrected the difference of the heading angles during the straight-line walking of pedestrians to suppress the error accumulation of the heading angle. Aiming at the particles that are severely divergent at the corners, a feature point matching algorithm was proposed to correct the pedestrian position error. Furthermore, the turning point extracted the main path that failed to match the current feature point map as a new feature point was added to update the map. Through the mutual modification of SLAM and an inertial navigation system (INS) the long-time, high-precision, and low-cost positioning functions of indoor pedestrians were realized.

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“…This is beneficial for the navigation of military vehicles. In summary, the magnetic navigation of vehicles has great prospects for development [2].…”

Section: Introductionmentioning

confidence: 99%

Feasibility Analysis of Magnetic Navigation for Vehicles

Huang

et al. 2019

Sensors

Self Cite

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Magnetic navigation is a promising positioning technique for scenarios where a global navigation satellite system (GNSS) is unavailable, such as for underwater submarines and aircraft in space. For ground scenarios, it faces more challenges, since the magnetic distribution suffers interference from surrounding objects such as buildings, bridges, and vehicles. It is natural to think how feasible it is to apply magnetic matching positioning to vehicles. In this paper, a theoretic distribution model is proposed to analyze the magnetic field around objects such as buildings, bridges, and vehicles. According to the experiments, it is shown that the proposed model matches the experimental data well. In addition, a comprehensive indicator metric is defined in this paper to describe the feasibility of the magnetic matching method based on the statistical characteristics of magnetic maps. The best length of matching window, anti-noise performance, and pre-comparison of positioning accuracy in different regions can be easily derived using the proposed comprehensive indicator metric. Finally, the metric is verified through a drive test using different building densities.

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A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model

Cited by 14 publications

References 19 publications

Integration of positioning and activity context information for lifelog in urban city area

Integration of positioning and activity context information for lifelog in urban city area

Research on PF-SLAM Indoor Pedestrian Localization Algorithm Based on Feature Point Map

Feasibility Analysis of Magnetic Navigation for Vehicles

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