论文部分内容阅读
对空域中弱小目标的探测是红外成像防御与制导的关键技术。由于空域中弱小目标距离较远,在红外探测器上呈现为无纹理特征的弱小点。由于红外探测器噪声与视场中杂波干扰,很难将目标从红外图像中提取出来。在红外空域弱小目标探测系统中,虚警率与探测率是一对矛盾的概念。针对这一问题提出了一种基于杂波模型估计理论的恒虚警(CFAR)检测技术。该CFAR技术是建立在对红外图像背景杂波分析建模的基础上,根据Neyman-Pearson准则设计CFAR检测器,实现在恒定虚警的前提下最大化追求系统的探测率,以此提高红外空域弱小目标探测系统的探测距离和目标识别能力。
The detection of weak targets in the airspace is the key technology of defensive and guidance of infrared imaging. Due to the distance between the weak and small targets in the airspace, the weak spot on the infrared detector appears as a texture-less feature. Due to the noise of the infrared detector and clutter interference in the field of view, it is difficult to extract the target from the infrared image. In the infrared airspace weak target detection system, the false alarm rate and the detection rate are a pair of contradictory concepts. A CFAR detection technique based on clutter model estimation theory is proposed for this problem. The CFAR technology is based on the background image clutter analysis of infrared images. Based on the Neyman-Pearson criterion, the CFAR detector is designed to maximize the detection rate of the system under the condition of constant false alarm so as to improve the infrared airspace Detection range and target recognition ability of weak target detection system.