基于恒虚警率的反卷积波束锐化方法

Beam sharpening approach based on constant false alarm rate and de-convolution

为了解决机场场面监视雷达(airport surface movement radar,ASMR)方位分辨率低的问题,在分析传统反卷积波束锐化方法局限性的基础上,提出了一种基于恒虚警率(constant false alarm rate,CFAR)的反卷积波束锐化方法。该方法采用CFAR处理自适应地调整反卷积处理的门限,避免迭代求解过程在低噪区域进行无效处理,在保证重点目标区域锐化效果的同时能抑制虚假小目标的发生,可有效降低AMSR系统的虚警率。计算机仿真分析及实测数据处理表明,本方法很好地解决了传统反卷积方法对噪声敏感的问题,具有重要的工程应用价值。

Based on the limitation analysis of conventional de-convolution approaches, an improved beam sharpening approach based on constant false alarm rate (CFAR) and de-convolution is proposed to deal with the poor resolution problem in azimuth direction of airport surface movement radar. Using the advantage of CFAR, the proposed method can adjust the processing threshold of de-convolution adaptively to avoid the uselessly iterative solving process in the noise region. Due to this improvement, it ensures the beam sharpening of targets in the interesting region and suppresses the occurrence of false targets simultaneously. At last the false rate of the airport surface movement radar (ASMR) system can be reduced effectively. The computer simulation analysis and real data processing show that our proposed algorithm can successfully solve the noise sensitivity in the conventional de-convolution approaches, and has important engineering application value.