Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2013.12.1767

Performance Improvement of a Pedestrian Dead Reckoning System using a Low Cost IMU  

Kim, Yun-Ki (Electrical Engineering, Pusan National University)
Park, Jae-Hyun (Electrical Engineering, Pusan National University)
Kwak, Hwy-Kuen (FCS Group, SAMSUNGTHALES)
Park, Sang-Hoon (FCS Group, SAMSUNGTHALES)
Lee, ChoonWoo (FCS Group, SAMSUNGTHALES)
Lee, Jang-Myung (Electrical Engineering, Pusan National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.6, 2013 , pp. 569-575 More about this Journal
Abstract
This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.
Keywords
IMU; pedestrian dead-reckoning; calibration; step detection; step length;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 C. Huang, Z. Liao, and L. Zhao, "Synergism of INS and PDR in self-contained pedestrian tracking with a miniature sensor module," IEEE Sensors Journal, vol. 10, no. 8, pp. 1349-1359, Aug. 2010.   DOI   ScienceOn
2 S. H. Fang and T. N. Lin, "Principal component localization in indoor WLAN environments," IEEE Trans. on Mobile Computing, vol. 11, no. 1, pp. 100-110, Jan. 2012.   DOI   ScienceOn
3 Y. Zhou, C. L. Law, Y. L. Guan, and F. Chin, "Indoor elliptical localization based on asynchronous UWB range measurement," IEEE Trans. on Instrumentation and Measurement, vol. 60, no. 1, pp. 248-257, Jan. 2011.   DOI   ScienceOn
4 J. Park and J. Lee, "A beacon color code scheduling for the localization of multiple robots," IEEE Trans. on Industrial Informatics, vol. 7, no. 3, pp. 467-475, Aug. 2011.   DOI   ScienceOn
5 J. Borenstein, L. Ojeda, and S. Kwanmuang, "Heuristic reduction of gyro drift for personnel tracking systems," The Journal of Navigation, vol. 62, no. 1, pp. 41-58, Jan. 2009.   DOI   ScienceOn
6 S. H. Shin, C. G. Park, and S. Choi, "New map-matching algorithm using virtual track for pedestrian dead reckoning," ETRI Journal, vol. 32, no. 6, pp. 891-900, Dec. 2010.   과학기술학회마을   DOI   ScienceOn
7 I. Skog, P. Handel, J. O. Nilsson, and J. Rantakokko, "Zero-Velocity detection-an algorithm evaluation," IEEE Trans. on Biomedical Engineering, vol. 57, no. 11, pp. 2657-2666, Nov. 2010.   DOI   ScienceOn
8 D. Alvarez, R. C. Gonzalez, A. Lopez, and J. C. Alvarez, "Comparison of step length estimators from weareable accelerometer devices," Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE, pp. 5964-5967, Nov. 2006.
9 Q. Ladetto, "On foot navigation: continuous step calibration using both complementary recursive prediction and adaptive Kalman filtering," Proc. of ION GPS 2000, pp. 1735-1740, Sep. 2000.
10 D. Alvarez, R. C. Gonzalez, A. Lopez, and J. C. Alvarez, "Comparison of step length estimators from wearable accelerometer devices," Proc. of the 28th IEEE EMBS Annual International Conference, pp. 5964-5967, Aug. 2006.
11 W. Chen, "An effective pedestrian dead reckoning algorithm using a unified heading error model," Position Location and Navigation Symposium, pp. 340-347, May 2010.
12 L. Fang, P. Antsaklis, L. Montestruque, M. McMickell, M. Lemmon, Y. Sun, H. Fang, I. Koutroulis, M. Haenggi, M. Xie, and X. Xie, "Design of a wireless assisted pedestrian dead reckoning system - the NavMote experience," IEEE Trans. Inst. and Meas., vol. 54, no. 6, pp. 2342-2358, 2005.   DOI   ScienceOn
13 W. Zijlstra and A. L. Hof, "Displacement of the pelvis during human walking: experimental data and model predictions," Gait & Posture, vol. 6, no. 3, p. 249, 1997.   DOI   ScienceOn
14 H. Weinberg, "Using the adxl202 in pedometer and personal navigation applications," Application Notes, American Devices, 2002.
15 S. Cho and C. Park, "MEMS based pedestrian navigation system," The Journal of Navigation, vol. 59, pp. 135-153, 2006.
16 S. P. Tseng, W. L. Li, C. Y. Sheng, J. W. Hsu, and C. S. Chen, "Motion and attitude estimation using inertial measurements with complementary filter," Proc. of 2011 8th Asian Control Conference(ASCC), May 2011.
17 H. G. Min, J. H. Yoon, J. H. Kim, S.-H. Kwon, and E. T. Jeung, "Design of complementary filter using least square method," Journal of Institute of Control Robotics and Systems (in Korean), pp. 125-130, Feb. 2011.   과학기술학회마을   DOI   ScienceOn
18 J. Y. Kim and S. Y Lee, "Estimation of the user's location/posture for mobile augmented reality," Journal of Institute of Control Robotics and Systems (in Korean), pp. 1011-1017, Nov. 2012.