Báo cáo hóa học: " Track-before-detect procedures for detection of extended object"

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: Track-before-detect procedures for detection of extended object | Fan et al. EURASIP Journal on Advances in Signal Processing 2011 2011 35 http content 2011 1 35 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Track-before-detect procedures for detection of extended object Ling Fan Xiaoling Zhang and Jun Shi Abstract In this article we present a particle filter PF -based track-before-detect PF TBD procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector the proposed algorithm performs joint estimation of the target presence absence trajectory and shape parameters under unknown nuisance parameters target power and noise variance . Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects. Keywords extended targets track-before-detect particle filter signal-to-noise ratio Introduction Most target tracking algorithms assume a single point positional measurement corresponding to a target at each scan. However high resolution sensors are able to supply the measurements of target extent in one or more dimensions. For example a high-resolution radar provides a useful measure of down-range extent given a reasonable signal-to-noise ratio SNR . The possibility to additionally make use of the high-resolution measurements is referred as extended object tracking 1 . Estimation of the object shape parameters is especially important for track maintenance 2 and for the object type classification. More recent approaches to tracking extended targets have been investigated by assuming that the measurements of target extent are available 1-5 . However the measurements of extended targets provided by the high resolution sensor are inaccurate in a low SNR environment since those are obtained by threshold-based decisions made on the raw measurement at each scan. Ristic et al. 3 investigated the influence

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