| 陈建峰,黄建国.一种改进的快速Mini-Norm算法[J].,1998,17(3):20-24 |
| 一种改进的快速Mini-Norm算法 |
| A modified fast algorithm for Mini-Norm direction-of-arrival estimation |
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| 中文摘要: |
| Kumaresan和Tufts提出的Mini－Norm算法（KT）通过对空间协方差矩阵进行特征分解，随后构造噪声子空间向量来求解方位。VictorT．Ermolaev和AlexB．Gershman在此基础上，利用指数基替代特征向量基建立了一种选代算法（VA），避免特征分解过程，从而减少了原算法的运算量。本文对该算法再进一步改进（FAST算法），合理简化参数设置，有效解决VA算法中的参量选取和选代收敛问题，使运算量又得到大幅度降低，更接近工程应用。文中介绍了FAST算法各参量的详细设置过程，利用计算机仿真与KT算法的性能进行统计分析比较。我们开展水池实验研究和VLSI实时运算实验来验证其实用性。各种结果均表明FAST算法性能优越，运算小，具有良好的应用前景。 |
| 英文摘要: |
| The original direction-of-arrival estimator, proposed by Kumaresan and Tufts (KT method), employs the noise-subspace projection matrix, calculated by the eigendecomposition of the spatial covariance matrix. A fast algorithm of this estimator is presented by V. T. Ermolaer and A. B. Gershman(VA method) which calculates the required mini-norm function using the special power basis instead of the eigenvector basis. In our paper, the VA method is further modified so as to simplify some parameter settings.After modification, the new method can efficiently implement the selection of parameters,confirm the convergence of the iteration and provide a substantial saving in the computational load as compared with those of KT method and VA method. Some computer simulation and experimental result are presented to verify the high performance and accuracy of the modified algorithm. |
| DOI：10.11684/j.issn.1000-310X.1998.03.005 |
| 中文关键词: 方位估计 特征子空间 Mini－Norm方法 |
| 英文关键词: Direction-of-arrival estimation Signal subspace Fast Mini-Norm lgorithm |
| 基金项目: |
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