CAJ | 학술논문

针对实际工程中风廓线雷达风向、风速随高度分布取值的非线性特性以及非气象干扰因素，基于非线性化方法---扩展卡尔曼滤波法，对风廓线雷达探测数据进行滤波处理。先利用泰勒展开式的一次项对非线性方程作线性化处理，再结合经典的卡尔曼滤波进行滤波估计，将非线性滤波问题转化为一个近似的线性滤波问题。仿真实验结果表明，该方法可以有效去除风场数据中掺杂的噪声干扰，很好地发挥了其非线性特性，滤波效果优于传统的卡尔曼滤波，具有一定的工程应用前景。
침대실제공정중풍곽선뢰체풍향、풍속수고도분포취치적비선성특성이급비기상간우인소，기우비선성화방법---확전잡이만려파법，대풍곽선뢰체탐측수거진행려파처리。선이용태륵전개식적일차항대비선성방정작선성화처리，재결합경전적잡이만려파진행려파고계，장비선성려파문제전화위일개근사적선성려파문제。방진실험결과표명，해방법가이유효거제풍장수거중참잡적조성간우，흔호지발휘료기비선성특성，려파효과우우전통적잡이만려파，구유일정적공정응용전경。
In view of nonlinear distribution characteristics of wind direction and wind speed with increase of height,as well as non-meteorological interference factors of wind profiler radar in engineering practices,a nonlinear method,namely Extended Kalman Filter ( EKF) is proposed in this paper for data filtering of wind profiler radar. U-sing first-order Taylor expansion and combining with the classic Kalman Filter ( KF ) , EKF method linearizes the nonlinear equations and changes the nonlinear filter into an approximately linear filter. The experimental results in-dicate that this method can effectively remove the noise of wind data and well reflects its nonlinear characteristics. EKF is better for data processing of wind profiler radar than traditional KF and has some engineering application prospects.