地波雷達與自動識別系統(tǒng)目標點跡最優(yōu)關聯(lián)算法
doi: 10.11999/JEIT140678 cstr: 32379.14.JEIT140678
基金項目:
國家自然科學基金(61362002)和海洋公益性科研專項(200905029)資助課題
Target Point Tracks Optimal Association Algorithm with Surface Wave Radar and Automatic Identification System
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摘要: 為了提高海洋探測精度和范圍，針對高頻地波雷達(HFSWR)和自動識別系統(tǒng)(AIS)目標點跡的融合利用問題，該文提出一種基于JVC(Jonker-Volgenant-Castanon)的點跡分狀態(tài)全局最優(yōu)關聯(lián)算法。首先，通過判斷高頻地波雷達和AIS點跡的徑向速度，將點跡分為準靜態(tài)目標和動態(tài)目標。接著，選取徑向速度和點跡間的球面距離為特征參數(shù)，對不同狀態(tài)下目標點跡分別進行徑向速度和位置間球面距離粗關聯(lián)。最后，使用相對距離比的平均值進行關聯(lián)效果的評價，通過選擇合適的關聯(lián)門限參數(shù)，使用JVC算法實現(xiàn)高頻地波雷達和AIS的點跡最優(yōu)關聯(lián)。實驗結(jié)果表明：該算法在關聯(lián)相同點跡對數(shù)的情況下，關聯(lián)精度高于最近鄰(NN)算法和Munkres關聯(lián)法，關聯(lián)用時少于最近鄰算法和Munkres關聯(lián)法。通過近3年內(nèi)3組不同時刻實測目標點跡的驗證，該算法可以滿足關聯(lián)的實用性和實時性要求。Abstract: In order to solve the problem that of High Frequency Surface Wave Radar (HFSWR) and Automatic Identification System (AIS) target point tracks fusion, a point tracks association algorithm using Jonker- Volgenant-Castanon (JVC) global optimal matching for different status is proposed. Firstly, the HFSWR and AIS target point tracks are divided into the quasi-static and dynamic data by the radial velocity. Then the radial velocity and spherical distance are selected as the feature parameters, and the different status data are respectively pre-associated by the radial velocity and spherical distance. Finally, the average of relative distance ratio is used to evaluate the effect of association. According to the selection of threshold parameter, the HFSWR and AIS point tracks are optimal associated with the JVC algorithm. The experimental results indicate that the proposed algorithm, in the condition of equal number point tracks associated, is superior to the Nearest Neighbor (NN) algorithm and Munkres association algorithm in the association accuracy, and the associate time is less than the NN algorithm and Munkres association. Moreover, three different time data gained from the target traits measured in nearly three years demonstrate that the feasibility and real-time of the proposed method.
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