摘要
机载雷达空时自适应处理(space-time adaptive processing,STAP)与单脉冲技术相结合可以实现对运动目标空、时参数的估计。然而,在非均匀环境下,由于同分布快拍数有限,杂波协方差矩阵难以准确估计,常常导致STAP方法性能急剧下降甚至失效,进而无法有效实现目标检测和参数估计。本文提出一种直接数据域的动目标空时参数估计方法,该方法首先应用幅相估计谱(amplitude and phase estimation,APES)谱估计由被检测单元数据估计出杂波干扰协方差矩阵,然后利用STAP技术抑制杂波和干扰,并结合单脉冲理论实现对目标角度和多普勒频率的估计。仿真结果表明,与传统单脉冲方法相比,新方法具有自适应抑制杂波干扰的能力和更好的估计性能;同时由于无需参考数据,该方法更适应于非均匀环境。
Space-time adaptive processing （STAP） for airborne radar combined with the monopulse technique can be used for estimating the spatial and temporal parameters of moving targets. However, in non-homogeneous environments, the clutter covariance matrix is difficult estimated accurately due to the amount of identically dis- tributed training data is limited. As a result, the performance of optimum STAP and its modified versions dra- matically decrease, especially those methods are failed. Additionally, in this case the effectively target detection and parameters estimation cannot be realized. A novel method is proposed for parameters adaptive estimation via no secondary data. This method calculates the covarianee matrix by applying the amplitude and phase estimation （APES） filter in the primary data firstly. Then, by combining STAP technique with the monopulse theory, the ground clutter is suppressed and the estimation of angle and Doppler frequency is obtained. Simulation results show that the proposed method has the capability of adaptive clutter suppression and can achieve accurate pa rameter estimation performance compared with the conventional monopulse method. This method is outstanding in severe non-homogeneous environments, because it does not need any secondary data.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2016年第12期2738-2744,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61231017
U1333106)
中央高校基本科研业务费(3122016D004)资助课题
关键词
机载雷达
空时自适应处理
单脉冲技术
非均匀杂波
airborne radar
space-time adaptive processing （STAP）
monopulse technique
non-homogeneousclutter
作者简介
王璐（1984-），女，讲师，硕士，主要研究方向为阵列信号处理、自适应天线技术。E-mail：luwang@cauc．edu．cn
吴仁彪（1966-），男，教授，博士，主要研究方向为自适应信号处理、谱估计方法。E-mail：rbwu@cauc．edu．cn
