一种用于多目标滤波的有效量测驱动序列蒙塔卡洛多伯努利滤波器

Tong-yang JIANG; Mei-qin LIU; Xie WANG; Sen-lin ZHANG

doi:10.1631/jzus.C1400025

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一种用于多目标滤波的有效量测驱动序列蒙塔卡洛多伯努利滤波器

计算机与自动化 | Updated：2022-05-19

- 一种用于多目标滤波的有效量测驱动序列蒙塔卡洛多伯努利滤波器
- An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering
- 信息与电子工程前沿（英文） 2014年15卷第6期页码：445-457
- Affiliations：
  
  1.State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
  2.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
- Author bio：
  
  [ "Tong-yang JIANG, E-mail: jiangtongyang@zju.edu.cn" ]
  Mei-qin LIU, E-mail: liumeiqin@zju.edu.cn
  [ "Xie WANG, E-mail: wangxiek@zju.edu.cn" ]
  [ "Sen-lin ZHANG, E-mail: slzhang@zju.edu.cn" ]
- Funds：
  
  Project supported by the National Natural Science Foundation of China (Nos. 61174142, 61222310, and 61374021), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Nos. 20120101110115 and 20130101110109), the Zhejiang Provincial Science and Technology Planning Projects of China (No. 2012C21044), the Marine Interdisciplinary Research Guiding Funds for Zhejiang University (No. 2012HY009B), the Fundamental Research Funds for the Central Universities (No. 2014XZZX003-12), and the Aeronautical Science Foundation of China (No. 20132076002)
- DOI：10.1631/jzus.C1400025
  中图分类号： TP391
- 收稿：2014-01-25，
  
  修回：2014-;5-;4，
  
  纸质出版：2014-06
- Accepted：
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一种用于多目标滤波的有效量测驱动序列蒙塔卡洛多伯努利滤波器[J]. 信息与电子工程前沿（英文）, 2014,15(6):445-457.

Tong-yang JIANG, Mei-qin LIU, Xie WANG, et al. An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(6): 445-457.
一种用于多目标滤波的有效量测驱动序列蒙塔卡洛多伯努利滤波器[J]. 信息与电子工程前沿（英文）, 2014,15(6):445-457. DOI： 10.1631/jzus.C1400025.

Tong-yang JIANG, Mei-qin LIU, Xie WANG, et al. An efficient measurement-driven sequential Monte Carlo multi-Bernoulli filter for multi-target filtering[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(6): 445-457. DOI： 10.1631/jzus.C1400025.

摘要

研究目的

序列蒙塔卡洛多伯努利滤波器的计算复杂度随量测个数线性增长，尤其在杂波环境下，量测中包含大量杂波量测，如果考虑所有的量测，将大大增加计算量，并且杂波量测也会降低滤波精度。因此，有必要从初始量测中区分可能的生存目标量测、新生目标量测和杂波量测，从而消除杂波量测，提高多目标滤波的实时性。

创新要点

利用跟踪门技术区分可能的生存目标量测、新生目标量测和杂波量测，之后用生存目标量测更新生存和新生目标，而新生目标量测只用来更新新生目标，从而在保证多目标滤波精度前提下，提高了多目标滤波的实时性。

方法提亮

首次利用跟踪门技术来区分可能的生存目标量测、新生目标量测和杂波量测，并提出了量测驱动方法用于序列蒙塔卡洛多伯努利滤波器。

重要结论

同初始的序列蒙塔卡洛多伯努利滤波器相比，本文所提方法在保证多目标滤波精度前提下，提高了多目标滤波的实时性。

Abstract

We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli (SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are distinguished from the original measurements using the gating technique. Then the survival measurements are used to update both survival and birth targets

and the birth measurements are used to update only the birth targets. Since most clutter measurements do not participate in the update step

the computing time is reduced significantly. Simulation results demonstrate that the proposed approach improves the real-time performance without degradation of filtering performance.

关键词

Keywords

references

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