一種基于水下無人航行器的多目標(biāo)被動跟蹤算法
doi: 10.11999/JEIT190675 cstr: 32379.14.JEIT190675
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1.
中國科學(xué)院聲學(xué)研究所 北京 100190
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2.
中國科學(xué)院先進水下信息技術(shù)重點實驗室 北京 100190
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3.
中國科學(xué)院大學(xué) 北京 100049
A Multi-target Passive Tracking Algorithm Based on Unmanned Underwater Vehicle
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1.
Institute of Acoustics of Chinese Academy of Sciences, Beijing 100190, China
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2.
Key Laboratory of Science and Technology on Advanced Underwater Information of Chinese Academy of Sciences, Beijing 100190, China
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3.
University of Chinese Academy of Sciences, Beijing 100049, China
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摘要:
被動聲吶信號處理中，致力于實現(xiàn)連續(xù)且穩(wěn)定的目標(biāo)方位跟蹤。在復(fù)雜的水下環(huán)境中，由于干擾和噪聲的存在，以及陣列孔徑的限制，方位檢測結(jié)果中不可避免地存在很多軌跡中斷、野值、干擾與目標(biāo)間的方位交叉。該文提出了一種基于水下無人航行器的多目標(biāo)被動跟蹤算法，使用基于航行器運動信息的粒子采樣預(yù)測方法進行軌跡中斷預(yù)測補齊，使用基于航行器運動信息的觀測門限設(shè)置方法自適應(yīng)設(shè)置跟蹤門限，使用塊關(guān)聯(lián)跟蹤方法進行軌跡中斷關(guān)聯(lián)和方位交叉關(guān)聯(lián)。仿真和實驗結(jié)果表明，該算法能夠?qū)崿F(xiàn)正確的多目標(biāo)跟蹤。
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關(guān)鍵詞:
- 被動聲吶 /
- 水下多目標(biāo)跟蹤 /
- 純方位跟蹤 /
- 水下無人航行器 /
- 純方位目標(biāo)運動分析 /
- 數(shù)據(jù)關(guān)聯(lián) /
- 粒子采樣
Abstract:In the passive tracking using acoustic arrays, continuous and stable tracking of targets is important. In complex underwater environments, there are inevitably many trajectory interruptions, outliers, interference and target azimuth crossings in the bearing detection results, due to interference, noise, and arrays aperture limitations. In this paper, a multi-target passive tracking algorithm based on unmanned underwater vehicle is proposed. The particle sampling prediction method based on the motion information of the vehicle is used to perform the interruption prediction. The observation threshold setting method based on the motion information of the vehicle is used to adaptively set the tracking threshold. The block association tracking method is used for association of trajectory break and azimuth cross. The experimental results show that the proposed algorithm achieves correct multi-target tracking.
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表 1 檢測概率和算法性能(%)
方位連續(xù)段
檢測概率算法正確
跟蹤概率方位連續(xù)段
檢測概率算法正確
跟蹤概率100 100.00 40 80.810 80 100.00 35 63.420 50 98.21 30 24.140 45 91.55 25 0.037 
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表 2 檢測跟蹤概率和平均方位誤差統(tǒng)計結(jié)果
閾值檢測 傳統(tǒng)跟蹤算法 VI-BOTA VIP-BOTA 檢測跟蹤概率(%) 64.85 69.67* 84.70* 92.62 平均方位誤差(°) 1.54 1.59 3.12(1.47) 1.29
下載: 導(dǎo)出CSV
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