• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.489-492
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• 2015

사용자의 위치기반 서비스에 대한 수요가 증가함에 따라 보행자의 현재 이동경로와 위치를 나타내는 '보행자 항법 시스템(PDR, Pedestrian Dead Reckoning)'에 관한 많은 연구들이 진행 중이다. 보행자 관성 항법 시스템은 IMU를 통해 데이터를 수신하여 각속도와 가속도 값을 구하고, 이 값을 토대로 사용자의 속도와 위치를 추정 한다. 또한 Zero-velocity(영속도)검출을 통해 누적되는 오차를 보정한다. 지금까지 대부분의 보행자 관성항법 시스템의 성능평가는 보행속도가 느리고 제한적인 상황에서 수행되었다. 하지만 이러한 상황은 보행자의 실제 보행상태를 반영하지 못한다. 본 논문에서는 다양한 보행속도에 따른 관성 항법 시스템의 성능을 실험하고 결과를 분석한다.

• ICROS
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• v.19 no.1
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• pp.32-48
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• 2013

최근 보행자와 차량의 항법 정보(위치, 속도, 자세, 방위각, 등)는 기존의 편의(convenience) 목적의 활용뿐 아니라 안전(safety) 보장을 위한 기반 정보로 활용되고 있으며 이에 대한 원천기술 및 활용기술의 연구개발이 활발하게 이루어지고 있다. 본 고에서는 인프라 기반 및 센서 기반의 다양한 보행자/차량용 항법 기술과 항법용 융합 필터 기술을 설명하고 연구사례를 살펴보고자 한다.

• Information and Communications Magazine
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• v.34 no.4
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• pp.17-24
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• 2017

본고에서는 저가형 관성 센서를 이용하여 실내 항법을 수행하는 여러 방법들에 대해 알아본다. 저가형 관성 센서를 이용한 추측 항법은 휴대성이 뛰어나고 외부의 인프라 없이 구현이 가능하고 가격이 저렴하다는 장점이 있지만, 오차가 빠르게 누적된다는 단점이 있다. 이를 해결하기 위해 사용자의 보행 특성을 이용한 보행자 추측 항법이 제안되었다. 본고에서는 보행자 추측 항법의 두 분류 기법인 걸음-이동방향 결합 기법과 관성 항법-영속도 보정 결합 기법의 원리와 각 기법들의 기술 동향에 대해 다루고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.143-144
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• 2016

본 논문은 보행자의 각 발에 부착된 2개의 IMU(Inertial Measurement Unit) 정보를 융합하여 위치 추적 성능을 향상시키는 보행자 추측 항법 알고리즘을 제안하였다. 센서내의 방향드리프트로 인해 IMU기반 보행자 위치추적은 시간이 지남에 따라 성능이 크게 저하된다. 제안하는 알고리즘은 방향 드리프트로 인해 각 발의 이동경로가 발산하는 점에 착안하여, 보폭이 일정 값을 초과할 시 이를 보정하고 사용자의 위치를 계산한다. 실험을 통해 제안하는 알고리즘이 방향 드리프트를 효과적으로 감소시키는 것을 확인하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5219-5226
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• 2014

This paper proposes an improved scheme of pedestrian position information system using neural network theory in a GPS-disabled area. Through a learning/obtaining gait pattern and step distance about walk, run, duck walk, crab walk and crawl, the position estimation error could be minimized by rejecting the inertial navigation drift. A portable hardware module was implemented to evaluate the performance of the proposed system. The performance and effectiveness of the suggested algorithm was verified by experiments indoors.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.3
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• pp.289-299
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• 2024

In the Pedestrian Dead Reckoning (PDR)/Global Positioning System (GPS)/Wi-Fi-integrated navigation system for indoor/outdoor continuous positioning of pedestrians, the process of detecting outliers in measurements is very important. When accurate location information from measurements is used, reliable correction data can be generated during the fusion filtering process. However, abnormal measurements may occur in certain situations, such as indoor/outdoor transitions, which can degrade filter performance and lead to significant errors in the estimated position. To address this issue, this paper proposes a method for detecting outliers in measurements based on Rényi Divergence (RD). When the deviation of the RD value is large, the measurements are considered outliers, and positioning is performed using only pure PDR. Based on experiments conducted with real data, it was confirmed that outliers were effectively detected for abnormal measurements, leading to an improvement in the performance of pedestrian navigation.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.521-534
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• 2021

Purpose: In this paper, we propose an indoor positioning scheme based on pedestrian dead reckoning using inertial measurement unit. By minimizing the effects of the orientation error of smart-phone, the more accurate estimation for the direction, the step count, and the stride can be achieved. Method: The effectiveness and the performance of the proposed scheme is evaluated by experiments, and it is compared with the conventional scheme in the same conditions. Result: The results showed that the positioning error of the proposed scheme was 0.76m, while that of the conventional scheme was 1.84m. Conclusion: Sine most people carry his/her own smart-phone, the proposed scheme can be helpful to recognize where he/she was and was heading when the fast evacuation is needed in indoors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.65-72
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• 2010

In this study, the performances of a medium grade IMU which is aimed for Mobile Mapping System and a low grade IMU for pedestrian navigation are analyzed through simulations under GPS signal blockage. In addition, an analysis on the accuracy improvement of barometer, electronic compass, or multi-sensor(combination of barometer and electronic compass) to correct medium grade or low grade IMU errors in the situation of GPS signal blockage is performed. With the medium grade IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 5m when the block time is over 30 seconds. When we correct IMU with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 60 seconds. In addition, barometer is more effective than the electronic compass when they are combined. In case of low grade IMU like MEMS IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 20m when the block time is over 15 seconds. When we correct INS with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 15 seconds in simulation results. On the contrary to medium grade IMU, electronic compass is more effective than the barometer in case of low velocity such as pedestrian navigation. It is expected that the analysis suggested a method to decrease position or attitude error using aided sensor integration when MMS or pedestrian navigation is operated under 1he environment of GPS signal blockage.