低空目标高分辨ISAR认知成像理论与方法研究

The problem of aerial target detecting and imaging has become the research hotspot to worldwide scholars. The ISAR imaging of low-altitude target is now regarded as one of the difficult problems because of the clutter and multipath effect. The project takes advantage of ISAR technique and compressed sensing theory in overcoming the effect of changeable clutter and multipath effect. In order to achieve the high-resolution ISAR imaging of low-altitude targets, the project puts forward the cognitive imaging theoretical framework based on compressed sensing and cognitive waveform design. The project will research on the clutter and multipath echo suppression strategy, clarify the requirement of sparse recovery for waveforms and propose the sparse representation method for target echo. And then, we choose and design appropriate compressed sensing imaging method based on the target scene feature, motion feature and scattering feature of the low-altitude targets. We will also study the influence rule of structured sparsity for echo reconstruction performance. The project will construct joint optimization model of cognitive waveform design and compressed sensing imaging method, uncover the influence rule of waveform optimization design and down-sampling strategy on the imaging effect. This project’s development and the research achievements will have important theoretical meaning and applicable value in promoting the development of low-altitude targets imaging.

对空中目标的探测和成像是当前国内外雷达技术研究的热点问题，而由于受到环境杂波和多径回波的影响，低空目标ISAR成像是当前研究的难点之一。本项目利用ISAR技术和压缩感知理论在抗杂波和多径问题中的优势，提出在认知成像理论框架下利用压缩感知理论和认知波形设计理论解决低空目标高分辨ISAR成像问题。项目将研究低空目标杂波和多径回波抑制策略，阐明稀疏重构对波形的特性需求，提出回波信号的稀疏表示方法；在此基础上针对低空目标的场景特点、运动特点和散射特点，选择设计合适的压缩感知成像方法，并研究结构化稀疏特性对回波重构性能的影响规律；项目将构建认知波形设计和压缩感知成像方法的联合优化模型，揭示波形优化设计和降采样策略对低空目标成像的作用机理，探索稀疏重构方法和最优波形设计的联合优化方案。本项目的开展及其研究成果对于促进低空目标成像技术的发展具有重要的理论意义和应用价值。

本项目本项目以低空目标高分辨ISAR成像为研究对象，综合考虑目标的环境特性和运动特性，也即杂波和多径的影响和目标的机动特性，将压缩感知理论和认知波形设计理论引入高分辨ISAR成像，探索低空目标高分辨成像的科学方法和途径。主要研究内容包括：对多径效应进行建模分析，通过数学化的描述分析多径对检测造成不利影响的原因，并对非理想噪声进行建模分析，为后续进行目标信号的处理和ISAR信号重构方法的设计奠定基础；针对目标特点选择合适信号波形，主要是对发射信号带宽进行选择设置；研究了基础多观测向量模式耦合的稀疏贝叶斯学习高分辨ISAR成像方法，该方法构造了多观测向量模式耦合模型，在该模型下，每一距离单元的高斯似然函数模型不仅与其对应的超参数相关，也与其对应的超参数的相邻参数相关，可获得优于传统稀疏贝叶斯重构方法的ISAR图像重构效果；针对低空目标信号特点，提出了基于二维块稀疏重构的成像方法，可获得优于传统方法的高分辨ISAR图像。研究成果共发表SCI检索论文7篇，EI检索论文2篇；以项目研究内容为基础申请并获得中国仿真学会优秀博士学位论文、陕西省优秀博士学位论文，获陕西省高等学校科学技术研究优秀成果二等奖1项，获陕西省科技工作者创新创业大赛二等奖1项。