射手模型优化与辨识及其对图像制导的影响

基于数据链通信的人在回路制导模式额外引入了射手动力学而且存在图像信号延时，含有射手动力学的控制回路会对目标在视场（LOS）中的误差角进行跟踪补偿，从而提升图像制导弹药的制导控制性能。为探究射手动力学和图像信号延时对人在回路制导性能的影响，基于真实的图像导引头模型及参数，设计校正网络以满足导引头稳定回路的性能需求；引入两类射手模型，针对射手模型2，优化模型结构并通过贴近真实环境的辨识实验得到动力学参数，弥补了现有建模的不足。基于射手对不同图像信号延时的适应性，对比研究了两类射手模型与不同图像信号延时对导引头控制系统稳定性、快速性和人在回路比例导引制导精度的影响。仿真结果表明：图像信号延时越长，导引头跟踪速度越低、误差角越大，制导系统的收敛时间越长；优化后的射手模型2及其参数辨识更准确地描述了射手的操作行为，对制导系统的影响较低且满足系统性能要求。

Optimization and identification of shooter model and its influence on image guidance

The human-in-the-loop guidance mode based on data link communication introduces additional shooter dynamics and has image signal delay, while the control loop with shooter dynamics will track and compensate the Line of Sight (LOS) angle error, thus directly improving the guidance and control performance of image guided ammunition. To explore the influence of shooter dynamics and image signal delay on human-in-the-loop guidance performance, a correction network is designed to meet the performance requirements of the seeker stability loop based on the real image seeker model and parameters. Two shooter models are introduced, with the shooter model 2, tructure optimized and dynamic parameters obtained via identification experiments in close-to-real environments, compensating for the shortcomings of the existing modeling. Based on the adaptability of the shooter to different image signal delays, the influence of two shooter models and different image signal delays on the stability, rapidity of the seeker and guidance precision of the human-in-the-loop proportional navigation guidance system are studied. The results show that the longer the image signal delay, the lower the seeker tracking speed, the larger the LOS angle error, and the longer the convergence time of the guidance system. The optimized second shooter model 2 and parameter identification more accurately describe the shooter behavior, which has a lower impact on the guidance system and meets the performance requirements of the system.