认知雷达转向控制系统优化设计研究

A Study on Optimal Design of Cognitive Radar Steering Control System

神经网络是一种模仿动物神经网络行为特征,进行分布式并行信息处理的算法数学模型。为了能更好地实现对认知雷达转向系统的精确控制,文中将神经网络的概念引入到认知雷达转向控制系统中,提出一种基于神经网络的认知雷达转向控制系统。首先介绍了神经网络的模型算法,然后基于此,对雷达转向系统进行跟踪仿真,进而得到预计的转向控制系统的输入量。最后,结合模型预测控制算法,对转向系统的角度和速度进行精确控制。为了验证理论分析结果,基于MATLAB搭建了认知雷达转向控制系统的仿真模型并进行仿真验证,结果表明,所提出的方法能够对转向系统的角度和速度进行精确控制,转矩脉动减小了56%,超调量减小了61%。

Neural network is an algorithmic mathematical model that imitates the behavioral characteristics of animal neural networks and performs distributed and parallel information processing.In order to better realize the precise control of the cognitive radar steering system,in this paper the concept of neural network is introduced into the cognitive radar steering control system,and a cognitive radar steering control system based on neural network is proposed.First,the neural network model algorithm is introduced,and then based on this,the radar steering system is tracked and simulated,and then the expected input of the steering control system is obtained.Furthermore,combined with the model predictive control algorithm,the angle and speed of the steering system are precisely controlled.In order to verify the theoretical analysis,in this paper a simulation model of the cognitive radar steering control system is built based on MATLAB and simulation verification is performed.The research results show that the method proposed in this paper can accurately control the angle and speed of the steering system,and the torque ripple has reduced by 56%,the amount of overshoot has been reduced by 61%.