本文为土耳其中东技术大学（作者：DUYGU ÇELEB）的硕士论文，共99页。
本文研究了单元平均CFAR（CA CFAR）雷达处理器的改进。提出了一种新的改进方法，在保证良好检测概率的同时，降低了虚警率。该方法利用了多普勒处理后出现的多普勒扩展特征，因此，这种方法被称为多普勒模式匹配（Doppler Pattern Matching，DPM）。通过蒙特卡洛仿真研究了该算法的性能。为了对算法性能进行评估，计算并对比了改进因子，即原始检测器虚警概率与改进检测器虚警概率之比。本文的研究表明，改进因子取决于仿真模拟场景的变化。在几乎所有仿真场景下，新算法都可以得到较好的改善因子。此外，在大多数情况下，将DPM应用于CA CFAR检测器之后，检测概率没有降低。
In this thesis, improvement of CellAveraging Constant False Alarm Rate (CA CFAR) radar processors is studied. Anew improvement method is proposed that will reduce probability of false alarmwhile keeping probability of detection at good values. This method makes use ofDoppler spreading patterns that appear after Doppler processing. Therefore thismethod is called Doppler Pattern Matching (DPM). Performance of the algorithmhas been investigated by Monte Carlosimulations. In order to evaluate the performance, improvement factor iscalculated which is the ratio of the probability of false alarm of originaldetector to the false alarm of improved detector. It is observed thatimprovement factor changes depending on the simulation scenario. Almost inevery case, good improvement factor can be obtained. Moreover, in most of thecases, there has been no reduction in probability of detection after DPM isapplied to CA CFAR detector.
1 引言
2 雷达信号处理基础
2.1 传统的雷达信号处理算法
2.2 非高斯分布与GLRT-LQ检测器
3 本文提出的新算法
3.1 多普勒处理方法
3.2 多普勒扩展的概念
3.3 DPM算法描述
3.4 新算法评述
4 仿真分析
4.1 仿真场景
4.2 仿真结果
5 结论
下载英文原文地址：
http://page5.dfpan.com/fs/5lcjc2212291563b178/
更多精彩文章请关注微信号：