کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6957226 | 1451915 | 2018 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Student-t mixture labeled multi-Bernoulli filter for multi-target tracking with heavy-tailed noise
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Student-t mixture labeled multi-Bernoulli filter for multi-target tracking with heavy-tailed noise Student-t mixture labeled multi-Bernoulli filter for multi-target tracking with heavy-tailed noise](/preview/png/6957226.png)
چکیده انگلیسی
A new labeled multi-Bernoulli (LMB) filter is proposed for multi-target tracking with joint heavy-tailed noises of the state and measurement. In contrast to the Gaussian assumption, the proposed method models both the process and measurement noises as multivariate Student-t distributions to handle the heavy-tailed noises. A closed form recursion of the LMB filter to propagate the parameters of Student-t mixture components is derived based on the multi-target Student-t models. Some approximations are applied to make the filter available in practice. The gating technique is also developed for the proposed method. Furthermore, a strategy of managing the number of Student-t components is introduced here to ensure the efficiency of the proposed method. Simulations with joint heavy-tailed noises of the state and measurement are performed to assess the proposed filter, and results demonstrate effectiveness of the new LMB filter.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 152, November 2018, Pages 331-339
Journal: Signal Processing - Volume 152, November 2018, Pages 331-339
نویسندگان
Peng Dong, Zhongliang Jing, Henry Leung, Kai Shen, Jinran Wang,