Accurate Target Motion Analysis from a Small Measurement Set Using RANSAC

Hyunhak SHIN  Bonhwa KU  Wooyoung HONG  Hanseok KO  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.6   pp.1711-1714
Publication Date: 2018/06/01
Publicized: 2018/02/23
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDL8245
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
bearing only target motion analysis,  RANSAC,  least squares,  

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Most conventional research on target motion analysis (TMA) based on least squares (LS) has focused on performing asymptotically unbiased estimation with inaccurate measurements. However, such research may often yield inaccurate estimation results when only a small set of measurement data is used. In this paper, we propose an accurate TMA method even with a small set of bearing measurements. First, a subset of measurements is selected by a random sample consensus (RANSAC) algorithm. Then, LS is applied to the selected subset to estimate target motion. Finally, to increase accuracy, the target motion estimation is refined through a bias compensation algorithm. Simulated results verify the effectiveness of the proposed method.