摘要
对于相控阵雷达抗主瓣干扰问题,本文通过对空时联合域抗主瓣干扰算法的研究,分析了基于阻塞矩阵预处理后常用的加权系数补偿法、白化法、对角加载法,以及对角加载结合线性约束波束保形算法存在的不足,提出了一种适用于采样快拍包含目标信号情况下的抗主瓣干扰算法。通过分析阻塞矩阵预处理后数据特征值的变化情况,修正预处理导致的过处理现象,从而重构协方差矩阵,该算法适用于阻塞矩阵预处理导致的自由度损失的情况,能够解决由于预处理导致的主瓣波峰偏移等失真问题,同时算法复杂度较低。该算法最大的优点是当采样快拍包含目标信号时,其抗干扰性能较好,快拍敏感度相比常规的波束保形方法更低,经实测数据验证,结果显示出该算法的优越性。
Regarding the main-lobe jamming suppression algorithm of phased array radar,the paper analyzes various anti-jamming algorithms based on blocking matrix pre-processing(BMP)according to the study of current main-lobe jamming suppression technique in the space-time domain,including the weighting coefficient compensation,whitening,diagonal loading and linear constraint combined with diagonal loading beam retention algorithms.A main-lobe jamming suppression algorithm for sampling snapshots containing target signals is proposed in this paper.By analyzing eigenvalues of the data after BMP,correcting the over-processing phenomenon,the covariance matrix is reconstructed.The modified CMR can not only be used in the case of the freedom loss caused by BMP,but also solve the distortion problems such as the main lobe peak offset in adaptive beam forming synthesis.The biggest advantage of the new algorithm is that its anti-jamming performance is excellent and stable when the sampling snapshot contains the target signal.Meanwhile,the algorithm complexity and the snapshot sensitivity are both at a low level.In the end,the verification results of the measured data also show the superiority of the proposed algorithm when the sampling snapshot contains the target signal.
作者
张萌
胡敏
宋万杰
张子敬
ZHANG Meng;HU Min;SONG Wanjie;ZHANG Zijing(National Key Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China;Wuhan Branch, Aerospace Nanhu Electronic Information Technology Co, Ltd, Wuhan 430000, China)
出处
《雷达科学与技术》
北大核心
2020年第3期233-238,246,共7页
Radar Science and Technology
基金
国家自然科学基金(No.61571349)。
关键词
相控阵雷达
抗主瓣干扰
阻塞矩阵预处理
协方差矩阵重构
实测数据
phased array radar
main lobe jamming suppression
blocking matrix pre-processing(BMP)
covariance matrix reconstruction(CMR)
measured data