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| 论文题目 |
一种新的基于UMVE和CA的恒虚警检测器 |
| 论文题目（英文） |
A Novel CFAR Detector Based on Unbiased Minimum-Variance Estimation and Cell Averaging |
| 作者 |
曲超 |
| 发表年度 |
2008 |
| 卷 |
25 |
| 期 |
9 |
| 页码 |
321-323 |
| 期刊名称 |
计算机仿真 |
| 摘要 |
在雷达自动检测系统中,通常是将自动检测和恒虚警 (CFAR)技术结合使用以保持在变化的杂波环境中获得可预测的检测性能和恒定虚警率。将无偏最小方差估计 (UMVE)方法和单元平均 (CA)方法结合,提出了一种新的恒虚警检测器(MUMCA - CFAR)。采用 UMVE和 CA方法产生两个局部估计,再取二者的平均值作为背景噪声功率水平估计。在 Swer2lingII型目标假设下,推导出MUMCA - CFAR在均匀背景下虚警概率和检测概率及多目标环境下检测概率的解析表达式,并与其它方法作了比较,结果表明该检测器在均匀背景和多目标环境下均具有相当优越的检测性能。
关键词:检测;恒虚警率;无偏最小方差估计;单元平均 |
| 摘要_英文 |
The technique of combining auto - detecti on with CFAR is frequently used in radar system, toget apredictable target detecti on probability at some false alarm rate cost in time - varying clutter situati ons . A new CFAR detect or (MUMCA - CFAR) based on unbiasedmini mum - variance esti mati on and cell averaging is p resented in this paper . It takes the sum of UMVE of leadingwindow and CA estimati on of laggingwindow as a global noise power estimati on . Under S werlingII assumption, the analytic expressi ons of false alarm probability and detecti on probability in homogeneous background are derived, and the analytic exp ressi on of detecti on probability in multiple target situati ons is also derived . In contrast to other detect ors, theMOS UM - CFAR detect or has fairly well detecti on performance in both homogeneous backgr ound and multiple target situati ons .
KEYWORDS:Detecti on; Constant false alarm rate (CFAR) ; Unbiased mini mum - variance esti mati on (UMVE) ;
Cell averaging (CA) |
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