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多目標(biāo)跟蹤中基于目標(biāo)威脅度評(píng)估的傳感器控制方法

陳輝,  賀忠良,  連峰,  李晨

陳輝, 賀忠良, 連峰, 李晨. 多目標(biāo)跟蹤中基于目標(biāo)威脅度評(píng)估的傳感器控制方法[J]. 電子與信息學(xué)報(bào), 2018, 40(12): 2861-2867. doi: 10.11999/JEIT180212
引用本文: 陳輝, 賀忠良, 連峰, 李晨. 多目標(biāo)跟蹤中基于目標(biāo)威脅度評(píng)估的傳感器控制方法[J]. 電子與信息學(xué)報(bào), 2018, 40(12): 2861-2867. doi: 10.11999/JEIT180212
Hui CHEN, Zhongliang HE, Feng LIAN, Chen LI. Threat Assessment Based Sensor Control for Multi-target Tracking[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2861-2867. doi: 10.11999/JEIT180212
Citation: Hui CHEN, Zhongliang HE, Feng LIAN, Chen LI. Threat Assessment Based Sensor Control for Multi-target Tracking[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2861-2867. doi: 10.11999/JEIT180212

多目標(biāo)跟蹤中基于目標(biāo)威脅度評(píng)估的傳感器控制方法

doi: 10.11999/JEIT180212 cstr: 32379.14.JEIT180212
  • 1.

    蘭州理工大學(xué)電氣工程與信息工程學(xué)院 ??蘭州 ??730050

  • 2.

    西安交通大學(xué)電子與信息工程學(xué)院 ??西安 ??710049

  • 3.

    西安交通大學(xué)軟件學(xué)院 ??西安 ??710049

基金項(xiàng)目: 國(guó)家自然科學(xué)基金( 61873116, 61370037, 61763029)，甘肅省科技計(jì)劃項(xiàng)目(18YF1GA065, 18JR3RA137)
詳細(xì)信息
    作者簡(jiǎn)介:

    陳輝：男，1978年生，教授，博士生導(dǎo)師，主要研究方向?yàn)槟繕?biāo)跟蹤和傳感器管理

    賀忠良：男，1993年生，碩士生，研究方向?yàn)槎嗄繕?biāo)跟蹤中的傳感器管理

    連峰：男，1981年生，副教授，博士生導(dǎo)師，主要研究方向?yàn)槎嘣葱畔⑷诤?、多目?biāo)跟蹤

    李晨：女，1981年生，講師，主要研究方向?yàn)槟繕?biāo)跟蹤

    通訊作者:

    陳輝　 huich78@hotmail.com

  • 中圖分類號(hào): TP274

Threat Assessment Based Sensor Control for Multi-target Tracking

  • 1.

    School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

  • 2.

    School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China

  • 3.

    School of Software Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Funds: The National Natural Science Foundation of China ( 61873116, 61370037, 61763029), The Gansu Provincial Science and Technology Planning (18YF1GA065, 18JR3RA137)
  • 摘要: 該文基于隨機(jī)有限集的多目標(biāo)濾波器提出一種基于目標(biāo)威脅度評(píng)估的傳感器控制策略。首先，在部分可觀測(cè)馬爾科夫決策過(guò)程(POMDP)的理論框架下，給出基于信息論的傳感器控制一般方法。其次，結(jié)合目標(biāo)運(yùn)動(dòng)態(tài)勢(shì)對(duì)影響目標(biāo)威脅度的因素進(jìn)行分析。然后，基于粒子多目標(biāo)濾波器估計(jì)多目標(biāo)狀態(tài)，依據(jù)多目標(biāo)運(yùn)動(dòng)態(tài)勢(shì)的評(píng)估研究建立多目標(biāo)威脅水平，并從多目標(biāo)分布特性中深入分析并提取出當(dāng)前時(shí)刻最大威脅度目標(biāo)的分布特性。最后，利用Rényi散度作為傳感器控制的評(píng)價(jià)指標(biāo)，以最大威脅度目標(biāo)的信息增益最大化為準(zhǔn)則進(jìn)行最終控制方案的求解。仿真實(shí)驗(yàn)驗(yàn)證了該方法的實(shí)用性和有效性。
    Abstract: This paper proposes a threat assessment based sensor control by using multi-target filter with random finite set. First, the general sensor control approach based on information theory is presented in the framework of Partially Observable Markov Decision Process (POMDP). Meanwhile, combined with target movement situation, the factors that affect the target threat degree are analyzed. Then, the multi-target state is estimated based on the particle multi-target filter, the multi-target threat level is established according to the multi-target motion situation, and the maximum threat target distribution characteristic is analyzed and extracted from the multi-target distribution characteristic. Finally, the Rényi divergence is used as the evaluation index in sensor control, and the final control policy is solved with the maximum information gain as the criterion. The simulation results verify the feasibility and effectiveness of the proposed method.
    • HTML全文

  • 圖  1  最大威脅目標(biāo)的粒子PHD原理圖

    圖  2  用來(lái)表示PHD的粒子云分布

    圖  3  實(shí)際的目標(biāo)軌跡

    圖  5  方案1中的傳感器軌跡控制

    圖  4  基于威脅評(píng)估的多目標(biāo)整體跟蹤效果

    圖  6  多目標(biāo)狀態(tài)估計(jì) OSPA 的比較

    圖  7  最大威脅度目標(biāo)狀態(tài)估計(jì)OSPA的比較

    圖  8  蒙特卡羅仿真中所有傳感器的位置

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    CHEN Hui, HE Zhongliang, and LIU Bei. Sensor control method based on information entropy measure for multi-target tracking[J]. Control and Decision, 2018, 33(2): 337–344 doi: 10.13195/j.kzyjc.2016.1424
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  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2018-03-05
  • 修回日期:  2018-08-13
  • 網(wǎng)絡(luò)出版日期:  2018-08-23
  • 刊出日期:  2018-12-01

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