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| 共形阵列LFM信号DOA和极化参数的联合估计 | |
| 引用本文： | 张树银,郭英,齐子森,苏令华. 共形阵列LFM信号DOA和极化参数的联合估计[J]. 应用科学学报, 2013, 31(3): 252-258. DOI: 10.3969/j.issn.0255-8297.2013.03.006 |
| 作者姓名： | 张树银 郭英 齐子森 苏令华 |
| 作者单位： | 空军工程大学电讯工程学院，西安710077 |
| 基金项目： | 国家自然科学基金(No.60601016)； 航空科学基金(No.20112096016)；陕西省自然科学基金(No.2010JQ8003)资助 |
| 摘 要： | 利用分数阶傅里叶变换(fractional Fourier transform, FRFT)对线性调频(linear frequency modulation,LFM)信号的能量匹配聚焦特性来简化共形阵列的数据模型，根据子空间拟合原理提出一种信源DOA和极化参数的去耦联合估计方法. 直接进行DOA估计涉及求解难度较大的多维多峰参数搜索过程，于是通过重构噪声子空间 和流形矩阵建立了单峰的目标函数，然后用PSO算法估计信源方位角和俯仰角，在此基础上利用ESPRIT实现极化参数估计. 仿真实验表明，去耦参数估计方法能在保证算法性能的前提下简化问题复杂度，有效降低运算量. |
| 关 键 词： | 线性调频信号 共形阵列天线 子空间拟合 粒子群优化 参数联合估计 |
| 收稿时间： | 2012-01-09 |
| 修稿时间： | 2012-04-04 |
Joint Estimation of DOA and Polarization for LFM Signals Using Conformal Array Antenna |
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| ZHANG Shu-yin,GUO Ying,QI Zi-sen,SU Ling-hua. Joint Estimation of DOA and Polarization for LFM Signals Using Conformal Array Antenna[J]. Journal of Applied Sciences, 2013, 31(3): 252-258. DOI: 10.3969/j.issn.0255-8297.2013.03.006 | |
| Authors: | ZHANG Shu-yin GUO Ying QI Zi-sen SU Ling-hua |
| Affiliation: | Institute of Telecommunication Engineering, Air Force Engineering University, Xi’an 710077, China |
| Abstract: | Using the energy concentration ability of fractional Fourier transform (FRFT) to linear frequency modulation (LFM) signal, this paper presents a simplified data model for conformal array, and proposes a method to de-couple DOA and polarization estimation using an algorithm of noise subspace fitting. As it uses a multi-dimensional and multi-peak search procedure to resolve the DOA estimation problem, the proposed scheme forms a single peak objection function by reforming the noise subspace vector and manifold matrix. 2D DOA estimation is performed with particle swarm optimization. The polarization parameter is then acquired based on the ESPRIT theory. Simulation results show that the proposed method can reduce the computation complexity with a favorable parameter estimation performance. |
| Keywords: | conformal array antenna (CAA) subspace fitting particle swarm optimization (PSO) joint parameter estimation linear frequency modulation (LFM) |
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