非理想条件下基于联合稀疏恢复的机载雷达杂波抑制方法研究

项目名称： 非理想条件下基于联合稀疏恢复的机载雷达杂波抑制方法研究

项目编号： No.61501506

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 段克清

作者单位： 中国人民解放军空军预警学院

项目金额： 18万元

中文摘要： 相比传统方法，稀疏恢复空时自适应处理（STAP）方法可改善机载雷达在非均匀杂波环境下的杂波抑制性能。然而，已有稀疏恢复方法研究侧重于单样本情况，且较少考虑各种非理想因素，因此在实际应用中存在较大性能损失。本项目主要研究适用于存在低杂噪比、系统误差、杂波起伏及非平稳杂波等非理想条件下的多观测样本联合稀疏恢复STAP方法。本项目的研究将稀疏恢复STAP方法的适用范围由理想条件拓展到实际应用背景，可望有效提升机载雷达在复杂地貌环境下的杂波抑制性能，并为我国现役机载雷达的改进和下一代新体制机载雷达的研制提供理论和关键技术支撑。

中文关键词： 空时自适应处理；稀疏恢复；机载雷达；杂波抑制；非理想条件

英文摘要： Compared with traditional methods, sparse recovery-based Space-time adaptive processing (STAP) methods can improve the clutter suppression ability under nonhomogeneous clutter environment. However, the existed methods recover the clutter spectrum only use single measurement data and ignore the influence of the nonideal measured data, thereby suffer from poor clutter cancellation performance in realistic airborne radar scenario. Here, we need to resovle the problem of sparse recovery-based clutter suppression under nonideal conditions. In details, we respectively research the multiple measurement data jointly sparse recovery-based STAP method considering of the influence of the low clutter-to-noise ratio, system errors, intrinsic clutter motion, and nonstationary clutter. The study will extend the scope of application of sparse recovery-based STAP method from ideal conditions to realistic nonideal situations, and significantly improve the clutter suppression ability under complicated geographical environment. Therefore, the study will proide the theory and key technology support for the improvement of the active airborne radar and the develoment of the next generation airborne radar.

英文关键词： space-time adaptive processing;sparse recovery;airborne radar;clutter suppression;nonideal condition