基于智能天线阵列的实用化高效超分辨测向技术研究

项目名称： 基于智能天线阵列的实用化高效超分辨测向技术研究

项目编号： No.61501142

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 闫锋刚

作者单位： 哈尔滨工业大学

项目金额： 23万元

中文摘要： 超分辨阵列测向技术虽然已经过近40年的蓬勃发展，但实践证明其工程化进程中尚有大量关键技术亟待攻克。其中，降低算法的计算量、提高算法的普适性是具有重要意义的研究工作之一。本项目以实用化为向导，拟对适用任意阵形和信号形式的高效超分辨阵列测向技术展开研究。首先，从典型阵形入手，分析导向矢量角度信息和阵列几何结构的耦合关系，结合电气、斜率和频率等变换域分析方法改进阵列测向的数据模型。其次，研究任意阵形下的矢量数据降维和空间谱搜索范围压缩方法，在此基础上论证以协方差矩阵分裂分解进行实值子空间估计的机理，探索二维优化问题的分批次一维化处理技术，以若干次一维测向实现二维阵列联合测向。最后，根据子空间统计特性，分析新算法的理论性能，推导其克拉美-罗下界和估计误差解析表达式。本项目研究结果将进一步丰富超分辨的理论内涵，同时将推进超分辨阵列测向技术的工程化应用进度。

中文关键词： 波达方向估计；空间谱估计

英文摘要： With a great prosperity and development in the last four decades, there are many critical problems to be solved in its real-world implementations for super-resolution direction-of-arrival (DOA) estimation techniques. Among, it is of great significance to reduce the computational complexity as well as to enhance the universality of DOA estimators. The present work focuses on practicability and high efficiency, which aims to propose a series of novel algorithms for one-dimensional and two-dimensional super-resolution DOA estimates. The manifolds of some typical arrays are first analyzed to reveal the coupling between DOA and array geometries, and three transformations in electrical domain, slope domain and frequency domain are proposed to improve the data model of DOA estimate. With these improved models and our previous works, two new methods based on dimension reduction and spectral compression, respectively, are developed for fast DOA estimation with arbitrary array configurations. Moreover, new schemes for low-complexity subspace decomposition with real-valued computations and fast two-dimensional DOA estimation with one dimensional search techniques are discussed. The statistical performance of proposed approaches are finally theoretically analyzed, and Cramér-Lower bound (CRLB) and Mean Square Error (MSE) expression for DOA estimation are derived. The research in the present work not only provides new meanings for super-resolution theory, but also offers significant contributions for the implementation of direction estimation.

英文关键词： Direction-of-Arrival Estimation;Spectral Estimation