摘要
针对分布式2D雷达组网的高度估计问题,提出了一种基于雷达局部航迹的目标高度估计方法.2D雷达由于不能获得目标的高度信息,其所得到的局部估计将会存在一定的系统误差.本文利用两部2D雷达的局部估计建立关于目标高度所产生系统误差的非线性模型.在此基础上,采用unscented Kalman filter(UKF)滤波方法实现对目标高度的实时估计.最后,采用蒙特卡洛仿真方法对新算法的性能进行分析.仿真结果表明,该方法的收敛速度较快,可以满足2D雷达网中目标高度估计的需要.
A new method based on the local radar track is presented in order to estimate the target height in distributed 2D radar network.Some system errors must exist in local estimation,because 2D radar can’t get the height information of target.It is shown that the nonlinear model for the error can be constructed through the local estimations of two 2D radars.Then,an unscented Kalman filter is used to estimate the target height in real time.At last,the Monte Carlo simulations are used to analyze the performance of the method.The simulation results show the proposed method has a faster convergence speed,and can efficiently meet the need of the height estimation in 2D radar network.
出处
《信息与控制》
CSCD
北大核心
2010年第4期408-412,共5页
Information and Control
基金
国家自然科学基金资助项目(60801049)
关键词
雷达组网
高度估计
不敏卡尔曼滤波
分布式
radar netting
height estimation
unscented Kalman filter
distributed
