红外云杂波下点目标检测算法性能评价  

Performance evaluation for point target detection algorithm under infrared cloud clutter

作　　者：巩晋南[1] 侯晴宇[1] 张伟[1] 

机构地区：[1]哈尔滨工业大学空间光学工程研究中心,黑龙江哈尔滨150001

出　　处：《哈尔滨工程大学学报》2015年第4期577-580,共4页Journal of Harbin Engineering University

基　　金：国家自然科学基金资助项目(61308100)

摘　　要：针对目前红外云杂波下点目标检测性能评价方法存在的局限性,提出了一种新的评价方法。首先,对影响检测性能的各要素,建立了杂波量化模型、探测器噪声模型和目标能量量化及传递模型;结合检测器理论,构造了算法性能表征参数。然后,将量化结果作为输入,利用基于遗传算法的BP神经网络建立量化结果与算法性能表征参数的数值关系。最后以Top-Hat算法和Butterworth滤波器为例,采用该方法评价并分析了其目标检测性能。实验表明,本方法误差在5×10-4以下,具有较高的评估精度。本方法将影响检测性能的耦合因素进行解耦合,通过该模型,不仅可以掌握算法性能变化规律,还能够为探测系统的总体设计和算法的选择提供依据,具有理论意义和工程应用价值。Aiming at the limitations of current performance evaluation methods for point target detection under infra-red cloud clutter, a new evaluation method is proposed.Firstly, for the elements that affect detection performance, the quantitative model of clutter, detector noise model, and quantitative and transfer model of target energy are con-structed;in combination with the detector theory, the algorithm＇s performance characterization parameter is built;then , using quantified results of the above models as inputs, the mathematical relationship between algorithm＇s per-formance characterization parameter and quantification results is developed using back-propagation （ BP ） neural network on the basis of genetic algorithm;finally, taking Top-Hat algorithm and Butterworth filter as an example, the method is applied to evaluate and analyze its target detection performance.Experimental results show that the error of the method is below 5×10^-4 , which shows high assessment accuracy.The proposed method uncouples the coupling factors influencing the detection performance for the first time.The proposed model is helpful for grasping the change law of the algorithm performance.The proposed model also provides the foundation for the general design of detection system and the selection of algorithms.It has theoretical significance and engineering application value.

关 键 词：点目标检测 云杂波 性能评价方法 杂波度量 量化模型 BP神经网络 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]