舰载机着舰引导雷达标校数据去噪方法研究  

Denoising Method for Landing Guidance Radar Calibration Data

作　　者：桑德一[1] 赵建军[1] 杨利斌[1] 

机构地区：[1]海军航空工程学院,烟台264001

出　　处：《计算机与数字工程》2015年第3期387-391,共5页Computer & Digital Engineering

摘　　要：舰载机着舰引导雷达要求精度高,必须定期进行标校。其标校数据中不仅含有多种雷达误差数据还包含多种噪声,且有些误差数据与噪声在频率上接近,普通的滤波算法不适合于着舰引导雷达标校数据去噪。研究了雷达标校数据的特点,提出了一种改进的EMD联合小波分解的去噪方法,根据标校数据特性改进了高低频分量判别函数和小波阈值函数。先对数据进行经验模态分解,再对分解后得到的高频分量进行小波阈值去噪,合并低频分量和去噪后的高频分量得到最终的去噪数据。仿真结果表明,该方法在保护了雷达误差数据的前提下,有效地去除了标校数据中的噪声。Landing guidance radar requires high precision,must be calibrated regularly.Calibration data contains many kinds of radar error data and a variety of noise,and some error data are close to the noise in frequency.So ordinary filtering algorithm is not suitable for the denoising of calibration data.An improved denoising algorithm is proposed based on EMD combined with wavelet decomposition in the premise of radar target characteristics of school data.The high frequency components of the discriminant function and wavelet threshold function are improved according to the calibration data characteristic.First the signal is devompased,then the high frequency components are denoised by wavelet.Finally,the low frequency components and the denoised high frequency components are combined to get the denoising data.The simulation results show that,the method removes the noise in the calibration data effectively in the premise of protection radar error data.

关 键 词：经验模态分解 小波变换 着舰引导雷达 阈值函数 去噪 

分 类 号：TN911.72[电子电信—通信与信息系统]