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

Ka Hyung Choi, Hyo Seok Cheon, Jin Bae Park, Tae Sung Yoon

Research output: Contribution to journalArticle


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.

Original languageEnglish
Pages (from-to)1077-1085
Number of pages9
JournalInternational Journal of Control, Automation and Systems
Issue number6
Publication statusPublished - 2012 Dec 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

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