3D雷达与2D雷达联合误差配准技术研究  

A Study on Collaborating Bias Alignment Technology for 3D Radar and 2D Radar

作　　者：陈垒[1] 孙伟[2] 王国宏[1] 郝欣[2] 

机构地区：[1]海军航空工程学院信息融合技术研究所,山东烟台264001 [2]南京电子技术研究所,南京210039

出　　处：《现代雷达》2010年第8期25-30,共6页Modern Radar

基　　金：国家自然基金资助项目(60972159);全国优秀博士学位论文作者专项基金资助项目(200443)

摘　　要：分析了地心地固(ECEF)坐标系下,两坐标(2D)雷达和三坐标(3D)雷达联合估计类误差配准方法和3D雷达校正2D雷达系统误差的方法。前者直接使用3D雷达和2D雷达的量测值,通过滤波得到各自的系统偏差估计值;后者则首先使用常规方法对2个3D雷达进行误差配准,然后使用配准后的3D雷达数据来校正2D雷达。2种算法都以卡尔曼滤波为基础构建等效量测方程和状态方程。根据2D雷达是否使用3D雷达提供的高度估计值,分2种情况进行公式推导和分析。仿真结果表明,联合类估计算法和不使用高度估计值的算法性能较好。Two kinds of bias alignment algorithms are deduced and simulated based on the Earth-centered-Earth-fixed（ECEF） coordinates,including the collaborating estimation algorithm between 3D（3-Dimension） and 2D radar and the algorithm of 3D radar correcting 2D radar.The former uses the measurements of 3D radar and 2D radar directly to obtain their systematic bias estimations respectively by filtering.The latter firstly uses ordinary method for two 3D radars to estimate their systematic biases.Then,it uses the registered data of 3D radar to rectify 2D radar.Both the two algorithms construct equivalent measurement equation and dynamic equation based on Kalman filtering.According to whether 2D radar uses the altitude information provided by 3D radar,there are two series of different formulas in both algorithms.Simulation results show that the collaborating estimation algorithm and the method of omitting altitude information at 2D radar have better estimation performance.

关 键 词：误差配准 ECEF坐标系 卡尔曼滤波 联合估计算法 校正算法 

分 类 号：TN95[电子电信—信号与信息处理]