摘要
利用单个旋转天线实现波束扫描高精度测角具有十分重要的意义。为了以低计算复杂度实现高精度角度估计,该文提出一种基于模式分量分离的闭式估计方法。首先将天线方向图表示为指数和形式,将角度估计问题转化为包含角度信息的模式分量估计问题,从而实现单模角度估计。结合模式分量的理论估计误差,推导得到多模联合估计式和理论估计精度。针对非理想观测条件下,模式分量求解出现的数值不稳定问题,提出对方向图进行匹配重构的方法,首先通过对观测序列和方向图抽样点进行互相关计算,估计得到粗略角度,确定方向图重构的角度范围,再通过匹配重构避免观测角度矩阵的病态问题。理论和仿真结果表明,所提的基于模式分量分离的多模测角方法具有估计精度高、计算简单的优点,提出的匹配重构方法提高了估计算法的适应性。
Estimation of Direction Of Arrival (DOA) with scanned beams of single rotational antenna is meaningful. To obtain precise estimation with low computation burden, a closed-form estimator is proposed based on estimating the mode component. Firstly, the problem can be transformed into the estimation of mode component when antenna pattern is expressed with a formula of exponential sums, thus DOA can be induced from each mode. Considering the estimation error, a multi-mode estimator with its theoretical error is derived. Non-ideal observing conditions result in an ill-determined problem for the estimation of mode component. A modified method is proposed by reconstructing the antenna pattern. By calculating cross-correlation of the observed amplitude trains with the antenna pattern samples, a coarse estimation of DOA is obtained to determine the angle range under the matched reconstruction. Then, ill-determined problem can be avoided if the converted mode component is calculated with the new pattern. Both theoretical and simulation results demonstrate that the proposed method can obtain high precise estimation with low computation cost, and the proposed matched reconstruction approach extends the adaptability of the method.
作者
朱晓丹
朱伟强
陈卓
ZHU Xiaodan1,2, ZHU Weiqiang1, CHEN Zhuo1 1(No.8511 Research Institute of China Aerospace Science and Industry Corporation, Nanjing 210007 ;2Graduate School of The Second Academy of China Aerospace, Beijing 100854, China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2018年第11期2691-2697,共7页
Journal of Electronics & Information Technology
关键词
测角
波束扫描
病态问题
互相关
模式分量
匹配重构
Direction finding
Beam scanning
Ill-determined problem
Cross-correlation
Mode component
Matched reconstruction