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兵工学报 ›› 2014, Vol. 35 ›› Issue (10): 1604-1611.doi: 10.3969/j.issn.1000-1093.2014.10.013

• 论文 • 上一篇    下一篇

跟踪窗自适应的捷联导引系统目标跟踪算法

郭晓冉1, 崔少辉1, 曹欢2, 杨锁昌1, 方丹1   

  1. (1.军械工程学院 导弹工程系河北 石家庄 050003;
  • 收稿日期:2013-12-25 修回日期:2013-12-25 上线日期:2014-11-28
  • 作者简介:郭晓冉(1985—)男博士研究生
  • 基金资助:
    军内科技创新项目(装司字\[2012\]665)

Target Tracking Algorithm of Strapdown Homing System Based on Adaptive Tracking Window

GUO Xiao-ran1,CUI Shao-hui1,CAO Huan2,YANG Suo-chang1,FANG Dan1   

  1. (1.Department of Missile Engineering, Ordnance Engineering College, Shijiazhuang 050003, Hebei, China;2.Beijing Aerospace Jiacheng Precision Technology Development Co., Ltd, Beijing 102600, China)
  • Received:2013-12-25 Revised:2013-12-25 Online:2014-11-28

摘要: 捷联图像末制导导弹在跟踪的后期阶段,弹目距离和成像视角的变化会引起图像尺度和旋转变化,目标区域将由小变大直至充满整个视场。针对经典的Mean Shift算法在图像制导目标跟踪过程中不能自适应目标的尺度和旋转变化这一问题,研究了一种跟踪窗自适应的Mean Shift目标跟踪算法。对初始选定的椭圆目标跟踪区域和候选区域进行加权操作,并利用权值图像的零阶矩和Bhattacharyya系数,对真实目标面积进行精确估计。利用估计出的目标真实面积,并结合权值图像的2阶中心矩进一步构建可表达目标窗口内图像特征的协方差矩阵,再通过奇异值分解建立椭圆面积与协方差矩阵特征值之间的关系,从而计算出椭圆目标区域实际的主轴长度和方向,实现跟踪窗的自适应变化。仿真实验结果表明,该方法既具有Mean Shift算法精度高、实时性好的特点,同时又扩展了Mean Shift算法在目标发生尺度和旋转变化时的自适应能力。

关键词: 兵器科学与技术, 图像制导, 捷联, Mean Shift算法, 矩特征, 自适应

Abstract: In strapdown imaging homing guidance system, the change of the distance between missile and target and the change of imaging visual angle may cause the rotation and scaling changes of image. The classical mean shift tracking algorithms can not robustly track a target which is under rotation and scaling. A scaling and rotation changing adaptive mean shift target tracking algorithm is proposed. The selected elliptic tracking region model and candidate tracking region model are weighted. Meanwhile, the moment characteristic and Bhattacharyya coefficient of weighted image are used to precisely estimate the actual area of target. Then a covariance matrix which can express the characteristic of image in tracking window is constructed using the estimated area and the second order center moment of weighted image. The relationship between the ellipse area and the eigenvalues of covariance matrix is established by singular value decomposition, the length and orientation of principal axis of ellipse are figured out, and the adaptive change of tracking window is realized. Test results indicate that this algorithm retains the high accuracy and real time of the classical mean shift algorithm, and at the same time, extends the adaptive ability of mean shift algorithm for the changes in scale and rotation of target.

Key words: ordnance science and technology, image guidance, strap-down, mean shift algorithms, moment feature, adaptation

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