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Augmented instrumental variable method for position and heading estimation with RDOA measurements

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  • Control Theory
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Abstract

In this paper, we proposed a position and heading estimation algorithm using only range difference of arrival (RDOA) measurements. Based on RDOA measurements, an uncertain linear measurement model is derived and both position and heading are estimated with the instrumental variable (IV) method which can show unbiased estimation results for the uncertainty of the model. In addition, to remove the unknown bias included in the measurement model error, we augment the bias to the state vector of the model. Since the proposition inherits the characteristic of the IV method, it does not need the stochastic information of the RDOA measurement excepting the assumption that the RDOA measurement noise is zero mean and white, and the zero mean error performance can be guaranteed when variances of RDOA measurement noises are identical. Through simulations, the performance of the proposed algorithm is verified at various positions and headings in the sensor network and compared with the robust least squares method which shows a zero mean error performance under the assumption that the stochastic information is known exactly.

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Yonsei University, Shinchondong, Seodaemun-gu, Seoul, Korea

    Ka Hyung Choi & Jin Bae Park

  2. Department of Electrical Engineering, Changwon National University, Sarimdong, Uichang-gu, Changwon-si, Gyeongsangnam-do, Korea

    Hyo Seok Cheon & Tae Sung Yoon

Authors
  1. Ka Hyung Choi
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  2. Hyo Seok Cheon
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  3. Jin Bae Park
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  4. Tae Sung Yoon
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Corresponding author

Correspondence to Tae Sung Yoon.

Additional information

Recommended by Editorial Board member Fuchun Sun under the direction of Editor Myotaeg Lim.

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0006107).

Ka Hyung Choi received his B.S. and M.S. degrees in Electrical and Electronic Engineering from Yonsei University, Seoul, Korea in 2006 and 2008, respectively. Currently, he is studying for his Ph.D. degree with the Dept. of Electrical and Electronic Engineering at Yonsei University, Seoul, Korea. His research interests include frequency estimation and localization.

Hyo Seok Cheon received his B.S. degree in Electrical Engineering from Changwon National University, Changwon, Korea, in 2010. His research interests include mobile robot localization, sensor network and vision.

Jin Bae Park received his B.S. degree in Electrical Engineering from Yonsei University, Seoul, Korea, in 1977 and his M.S. and Ph.D. degrees in Electrical Engineering from Kansas State University, Manhattan, in 1985 and 1990, respectively. Since 1992, he has been with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, where he is currently a Professor. His research interests include robust control and filtering, nonlinear control, mobile robot, fuzzy logic control, neural networks and genetic algorithms. He is serving as vice-president for the Institute of Control, Robotics and Systems. He had served as an Editor-in-chief for the International Journal of Control, Automation and Systems from 2006 to 2010.

Tae Sung Yoon received his B.E., M.S., and Ph.D. degrees in Electrical Engineering from Yonsei University, Seoul, Korea, in 1978, 1980, and 1988, respectively. He was with the Department of Electrical Engineering, the 2nd Naval Academy, Jinhae, Korea, as a member of the teaching staff from 1980 to 1983, and was with the Department of Electrical Engineering, Vanderbilt University, Nashville, TN, as a Visiting Assistant Professor from 1994 to 1995. Since 1989, he has been with the Department of Electrical Engineering, Changwon National University, Changwon, Korea, where he is currently a Professor. His research interests include robust filtering, mobile robot, and time-frequency signal processing in instrumentation.

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Choi, K.H., Cheon, H.S., Park, J.B. et al. Augmented instrumental variable method for position and heading estimation with RDOA measurements. Int. J. Control Autom. Syst. 10, 1077–1085 (2012). https://doi.org/10.1007/s12555-012-0601-4

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  • DOI: https://doi.org/10.1007/s12555-012-0601-4

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