机载雷达前视探测方位超分辨算法  

The Super-resolution Algorithm in Azimuth for Airborne Radar Forward-looking Detection

作　　者：管金称[1] 杨建宇[1] 黄钰林[1] 李文超[1] 

机构地区：[1]电子科技大学电子工程学院,四川成都611731

出　　处：《信号处理》2014年第12期1450-1456,共7页Journal of Signal Processing

基　　金：国防基础科研研究计划(B1420110182);国家自然科学基金(61301273)

摘　　要：机载雷达前视探测在民用与军用领域都具有广泛应用,例如跑道障碍物探测、低空飞行、自主着陆、侦察等。由于探测区域方位向多普勒带宽几乎为零,不满足DBS与SAR技术处理的条件,因此方位分辨率由天线波束3d B宽度决定。针对雷达前视探测方位低分辨率问题,本文提出一种基于改进雷达信号模型的统计优化超分辨算法。算法同时利用泊松与高斯噪声的分布先验信息进行数学建模,选择贝叶斯最大似然准则对超分辨反问题正则化,通过近似迭代求解实现雷达方位向超分辨。仿真与实测数据结果表明,与改进维纳滤波算法相比较,该算法降低了噪声敏感性,有效抑制虚假目标产生,对于提高波束主瓣内目标分辨能力具有实际应用意义。Airborne radar forward-looking detection has a wide range of civil and military applications,such as runway obstacle detection,low-altitude flight,autonomous landing,scout.Because the Doppler bandwidth of the forward-looking detection area is almost zero,DBS and SAR technique is not satisfied with the condition.Then the azimuth resolution is de-termined by the 3dB beam width of the antenna.Aiming at the issue of low resolution in azimuth for airborne radar forward-looking detection,this paper presented a statistical optimization super-resolution algorithm based on an improved signal model.Bayesian maximum likelihood selection is selected to regularize the super-resolution inverse problem,Poisson and Gaussian noise distribution are used as priori information for mathematical modeling,and approximation iterative solutions are chosen to achieve radar super-resolution in azimuth.Compared with the improved Wiener filter algorithm,simulations and real radar data result verify that the algorithm reduces the noise sensitivity further,effectively suppresses generating of false targets,and improves the ability of distinguishing targets with practical applications within the main lobe.

关 键 词：机载雷达 前视探测 方位超分辨 最大似然 

分 类 号：TN957.2[电子电信—信号与信息处理]