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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 217373 13 pages doi 10.1155 2008 217373 Research Article Sequential Monte Carlo Methods for Joint Detection and Tracking of Multiaspect Targets in Infrared Radar Images Marcelo G. S. Bruno Rafael V. Araujo and Anton G. Pavlov Instituto Tecnológico de Aeronautica Sao Jose dos Campos SP 12228 Brazil Correspondence should be addressed to Marcelo G. S. Bruno bruno@ele.ita.br Received 30 March 2007 Accepted 7 August 2007 Recommended by Yvo Boers We present in this paper a sequential Monte Carlo methodology for joint detection and tracking of a multiaspect target in image sequences. Unlike the traditional contact association approach found in the literature the proposed methodology enables integrated multiframe target detection and tracking incorporating the statistical models for target aspect target motion and background clutter. Two implementations of the proposed algorithm are discussed using respectively a resample-move RS particle filter and an auxiliary particle filter APF . Our simulation results suggest that the APF configuration outperforms slightly the RS filter in scenarios of stealthy targets. Copyright 2008 Marcelo G. S. Bruno et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION This paper investigates the use of sequential Monte Carlo filters 1 for joint multiframe detection and tracking of randomly changing multiaspect targets in a sequence of heavily cluttered remote sensing images generated by an infrared airborne radar IRAR 2 . For simplicity we restrict the discussion primarily to a single target scenario and indicate briefly how the proposed algorithms could be modified for multiobject tracking. Most conventional approaches to target tracking in images 3 are based on .
