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X. Lin, T. Kirubarajan and Y. Bar-Shalom, “Multisensor Bias Estimation Using Local Tracks without a Priori Association,” Proceedings of SPIE Conference on Signal and Data Processing of Small Targets, Vol. 5204, 2003, pp. 334-345. doi:10.1117/12.503715

has been cited by the following article:

• TITLE: Track-to-Track Association Technique in Radar Network in the Presence of Systematic Errors

  AUTHORS: Jian Yang, Qiang Song, Changwen Qu, You He

  KEYWORDS: Systematic Errors; Phase Correlation; Track-to-Track Association; Sensor Registration; Radar Network

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.4 No.3, August 15, 2013

  ABSTRACT: The presence of systematic measuring errors complicates track-to-track association, spatially separates the tracks that correspond to the same true target, and seriously decline the performances of traditional track-to-track association algorithms. Consequently, the influence of radar systematic errors on tracks from different radars, which is described as some rotation and translation, has been analyzed theoretically in this paper. In addition, a novel approach named alignment-correlation method is developed to estimate and reduce this effect, align and correlate tracks accurately without prior registration using phase correlation technique and statistic binary track correlation algorithm. Monte-Carlo simulation results illustrate that the proposed algorithm has good performance in solving the track-to-track association problem with systematic errors in radar network and could provide effective and reliable associated tracks for the next step of registration.