交会末段制导引信一体化系统射频成像目标轮廓重构方法
Terminal Target Contour Reconstruction Algorithm Based on RF Imaging for GIF
查看参考文献16篇
|
文摘
|
目标实时精确识别与定位是实现制导引信一体化(GIF)技术的关键,对提高弹药末制导及起爆控制精度具有决定性的意义。以射频成像GIF体制为对象,基于射频成像原理及目标特性,结合计算几何和统计学原理,针对交会末段提出了一种目标轮廓重构方法。该方法通过灰度映射变换,提取仅包含目标信息的灰度值,显著降低了数据量,同时增强了图像对比度;在阈值分割、角点提取的基础上,应用统计学剔除异常值的方法滤除背景噪声并抑制目标边界干扰;利用凸壳技术实现目标轮廓重构,得到可以完全覆盖目标区域的最优凸多边形作为目标轮廓。理论分析和仿真结果表明,该方法时间复杂度低,实时性好,可实现目标的精确识别与定位。 |
|
其他语种文摘
|
The real-time accurate target recognition and localization are the key factors to implement the guidance integrated fuzing (GIF) technique and enhance the performance of terminal guidance and the accuracy of burst control. A real-time and accurate terminal target contour reconstruction algorithm for RF imaging GIF technique is proposed based on the principle of RF imaging and the target properties. The gray values with target information are extracted by gray mapping transform, thus decreasing the data quantity and the power-law transformation for image enhancement. Based on threshold segmentation and corner detection, the statistical methods are utilized to filter the background noise and suppress the target boundary interference. The target contour reconstruction is achieved by the convex hull technique, which is the optimal convex coveringa target area. Both the simulation and theoretical analysis results show that the time complexity of the proposed algorithm is lower, thus it can be used to achieved the real-time and accurate terminal target recognition and localization for RF imaging GIF. |
|
来源
|
兵工学报
,2015,36(9):1624-1631 【核心库】
|
|
DOI
|
10.3969/j.issn.1000-1093.2015.09.004
|
|
关键词
|
兵器科学与技术
;
导航制导
;
制导引信一体化
;
目标识别
;
异常值点
;
计算几何
;
凸壳
|
|
地址
|
1.
北京理工大学机电学院, 北京, 100081
2.
上海无线电设备研究所, 上海, 200090
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1000-1093 |
|
学科
|
武器工业;航空 |
|
基金
|
航天科技创新基金
|
|
文献收藏号
|
CSCD:5560143
|
参考文献 共
16
共1页
|
|
1.
Chopper K. Guidance integrated fuzing analysis and simulation.
First IEEE Conference on Control Applications,1992:750-755
|
CSCD被引
2
次
|
|
|
|
|
2.
孙博. 防空导弹红外成像制导引信一体化应用研究.
弹箭与制导学报,2012,33(1):57-60
|
CSCD被引
1
次
|
|
|
|
|
3.
Fan M G. Prediction of time to go of IR Imaging GIF.
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications,2011:81931-81934
|
CSCD被引
1
次
|
|
|
|
|
4.
刘斌. 基于成像导引/激光测距的起爆控制算法.
探测与控制学报,2012,34(2):57-60
|
CSCD被引
7
次
|
|
|
|
|
5.
Li L J. A new method to select aimpoint for airplane target at end term.
Proceedings of SPIE, 8918,2013:1-6
|
CSCD被引
1
次
|
|
|
|
|
6.
朱顺安.
图像边缘检测并行算法的研究和基于FPGA的实现,2013
|
CSCD被引
1
次
|
|
|
|
|
7.
Waghule D R. Overview on edge detection methods.
International Conference on Electronic Systems, Signal Processing and Computing Technologies,2014:151-155
|
CSCD被引
1
次
|
|
|
|
|
8.
曹传东. 基于力场转换理论的图像粗大边缘检测方法.
航空学报,2011,32(5):891-899
|
CSCD被引
5
次
|
|
|
|
|
9.
Mashford J. Edge detection in pipe images using classification of haar wavelet reansforms.
Applied Artificial Intelligence,2014,28(7):675-689
|
CSCD被引
2
次
|
|
|
|
|
10.
Mahalanobis A. Correlation filters for object tracking target reacquisition and smart aimpoint selection.
SPIE Journal,1997,3073:25-32
|
CSCD被引
1
次
|
|
|
|
|
11.
周培德. 红外图像边缘提取的算法.
兵工学报,2007,28(5):524-527
|
CSCD被引
2
次
|
|
|
|
|
12.
Tsang P. Affine invariant matching of broken boundaries based on simple genetic algorithm and contour reconstruction.
Pattern Recognition Letters,2010,31(9):771-780
|
CSCD被引
4
次
|
|
|
|
|
13.
Tsang P. Enhanced affine invariant matching of broken boundaries based on particle swarm optimization and the dynamic migrant principle.
Applied Soft Computing,2010,10(2):432-438
|
CSCD被引
2
次
|
|
|
|
|
14.
Martinez A. Edge detection from non-uniform Fourier data using the convolutional gridding algorithm.
Journal of Scientific Computing,2014,61(3):490-512
|
CSCD被引
3
次
|
|
|
|
|
15.
谢锐. 外辐射源天地波雷达定位方法及精度分析.
电波科学学报,2014,29(3):442-449
|
CSCD被引
6
次
|
|
|
|
|
16.
赵连军. 单目三点位置测量精度分析.
光学精密工程,2014,22(5):1190-1197
|
CSCD被引
12
次
|
|
|
|
|
了解气象卫星更多信息，请访问