单元筛选后作最小选择的CFAR自适应检测器

Modified SO-CFAR adaptive detector based on cell selection

为提高雷达自适应检测能力,本文针对多个干扰目标背景提出一种新的CFAR自适应检测方法。在斯威林2型目标的假设下对这种检测方法进行了检测性能分析,理论推导出均匀杂波背景和强干扰目标存在的情况下虚警概率和检测概率的数学模型,并把它同CA、GO、SO(smallestof)等检测方法用MATLAB仿真软件进行了比较。结果表明,这种方法在均匀杂波背景和多个干扰目标背景情况下都有很好的检测性能,尤其是多目标干扰条件下具有更大的优势。

To improve the radar adaptive detection performance in multiple interfering targets environments,a new CFAR detector is proposed and its detection performance is analyzed under the Swerling 2 assumption.The models for false alarm rate and detection probabilities in homogeneous clutter background and in the presence of strong interfering targets are theoretically deduced and are compared using MATLAB to other detection methods such as CA-CFAR,GO-CFAR and SO-CFAR,etc.The results indicate that the new method has favorable detection performance in both homogeneous clutter backgrounds and multi-target environments and especially has superiorities in multi-target environments.