先验信息不确定条件下雷达目标检测迭代波形优化方法

Affected by uncertain prior information, the low-altitude detection of radar seekers becomes unstable, resulting in a significant drop in the success rate of air defense missiles intercepting low-altitude targets. Iterative waveform design can systematically improve the accuracy of prior information. Jointly considering the iterative characteristics between the prior information of the target and the environment, the main scientific problems in this research are the iterative mechanism between target perception and clutter suppression, and the nonlinear variation mechanism of the constraint waveform affecting the SINR performance. By solving these problems, we can get an iterative waveform optimization method for target detection under uncertain prior information conditions. Firstly, the key factors affecting the target detection performance are analyzed, the multipath effect of specular and diffuse multipath is explored, and the relationship model between low-altitude characteristics and target detection performance is established. And then, in order to solve the three prior information uncertainties such as target, clutter, target and clutter, new waveform optimization criteria based on worst-case optimization, stochastic optimization and average mutual information design are constructed. Finally, a multi-constrained target detection performance prediction model is established, a cognitive optimization waveform optimization strategy is studied, and a multi-criteria multi-constrained robust waveform optimization method is proposed. The results of the project will provide a theoretical basis and technical support for solving the problem of the low-altitude radar target detection, which is of great significance for enhancing the anti-air-strike capability in China.

受不确定先验信息影响，雷达导引头的低空检测变得不稳定，致使防空导弹对低空目标的拦截概率大幅下降，迭代波形设计能从体制上提升先验信息的准确性。本项目将综合考虑目标和环境先验信息间的迭代特性，通过突破目标感知和杂波抑制间的迭代机制、约束波形影响SINR性能的非线性变化机理等关键问题，提出不确定先验信息条件下目标检测迭代波形优化方法。研究内容包括剖析影响目标检测性能的关键因素，探索镜像和漫多径共同作用的多径效应，建立低空目标环境特性与目标检测性能的关系模型；针对目标、杂波、目标和杂波等三种先验信息不确定情况，分别基于worse-case优化、stochastic优化、平均信息量构建新的波形优化准则；建立多约束条件的目标检测性能预测模型，研究认知反馈的波形优化策略，提出多准则多约束的鲁棒波形优化方法。项目预期成果将为解决低空目标检测难题提供理论基础和技术支撑，对提升我国反低空突防能力具有重要意义。

受不确定先验信息影响，雷达导引头的低空检测变得不稳定，致使防空导弹对低空目标的拦截概率大幅下降，迭代波形设计能从体制上提升先验信息的准确性。本项目围绕先验信息不确定条件下雷达目标检测迭代波形优化方法开展研究，主要研究成果包括：（1）改进构建了面向目标检测的自适应匹配波形设计框架，建立了互信息、相关熵和信干噪比等波形优化准则之间的频域约束关系模型，提出了信号相关杂波背景下基于信息论的频域波形设计方法，为弹载雷达有限能量分配提供了优化策略。（2）提出了用于角度估计的DOA信息理论模型，构建了信噪比约束下最大化DOA信息的目标函数，设计了基于最大值最小化方法的自适应波形优化算法，有效降低了导弹目标相对运动时，目标先验信息的起伏度。（3）提出了以代表检测概率的相关熵为波形设计准则，以代表虚警概率的相关熵、信噪比建立约束条件，构建了相关熵和信噪比共同约束的波形设计目标函数，设计了一种多约束条件的波形优化算法，所提算法只涉及特征向量计算，缩减了计算复杂度。（4）针对弹载雷达多任务耦合迭代，提出了基于双阶段信息论准则的多目标检测波形设计方法，设计了用于多目标检测的自适应波形优化算法。项目基于认知理论和信息论框架，研究低空条件下雷达导引头对目标检测的匹配波形设计方法，为解决低空目标检测难题提供理论基础和技术支撑，对提升我国反低空突防能力具有重要意义。