کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
757884 1462518 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel variable-lag probability hypothesis density smoother for multi-target tracking
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
پیش نمایش صفحه اول مقاله
A novel variable-lag probability hypothesis density smoother for multi-target tracking
چکیده انگلیسی

It is understood that the forward–backward probability hypothesis density (PHD) smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality (i.e., the number of targets) estimate. This is because backward smoothing ignores the effect of temporary track dropping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chinese Journal of Aeronautics - Volume 26, Issue 4, August 2013, Pages 1029–1037
نویسندگان
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