电讯技术2016，Vol.56Issue(5)：575-580,6.DOI:10.3969/j.issn.1001-893x.2016.05.017
基于地形融合分类的分区二维恒虚警检测器
A Partition Two-dimensional Constant False Alarm Rate Detector Based on Terrain Fusion Classification
彭馨仪1
作者信息
- 1. 中国西南电子技术研究所，成都610036
- 折叠
摘要
Abstract
In heterogeneous clutter background the constant false alarm rate( CFAR) detectors always mis-match the actual clutter background characteristics which lead to a sharp decline in the detector perform-ance. In order to solve the problem, a partition two-dimensional CFAR detector based on terrain fusion classification is proposed. Firstly,a terrain fusion classification algorithm is proposed based on the goodness of fit( GoF) to realize the terrain classification numbering under complex heterogeneous clutter and the am-plitude distribution and amplitude distribution parameters recording. And then with the numbered terrain and the recorded amplitude distribution, CFAR processing window selects the amplitude distribution matched CFAR detector to achieve the two-dimensional partitions CFAR. Finally, the measured data proves the effectiveness of the terrain fusion classification algorithm. The half measured data and measured data is provided to demonstrate the performance of the proposed CFAR detector,and the result shows that compared with the traditional two-dimensional CFAR detector,the proposed one has significant improve-ment in heterogeneous clutter background.关键词
分区二维恒虚警检测/地形融合分类/非均匀杂波/拟合优度Key words
partition two-dimensional constant false alarm rate detection/terrain fusion classification/het-erogeneous clutter/goodness of fit分类
信息技术与安全科学引用本文复制引用
彭馨仪..基于地形融合分类的分区二维恒虚警检测器[J].电讯技术,2016,56(5):575-580,6.
