| 淦华东,李志舜,王惠刚.一种自适应最小范数算法[J].,2005,24(5):317-321 |
| 一种自适应最小范数算法 |
| An adaptive mini-norm algorithm |
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| 中文摘要: |
| 运用特征子空间方法的关键在于信号子空间或噪声子空间的估计,实际上有些信号的统计特性随时间变化,于是要求得到参数的实时估计值,为此,需要随时根据新的阵列接收数据对信号或噪声子空间进行更新。本文首先分析了一种自适应子空间估计算法,即MALASE(MaximumLikelihoodAdaptiveSubspaceEstimation)算法。然后,把MALASE算法与传统的最小范数(Mini-Norm)高分辨算法相结合,并应用零点跟踪技术,提出了一种自适应Mini-Norm高分辨算法,可用于对时变的信号波达方向(DOA)进行跟踪估计。计算机仿真结果验证了该算法的有效性。 |
| 英文摘要: |
| The key problem of eigen subspace methods is the estimation of signal or noise subspace. In practical situations, there exist signals whose statistic characteristics always change over time. To obtain the real time estimates of the signal parameters which are time varying, it is necessary to update the signal or noise subspace according to newly received array sampled output. In this paper, an algorithm MALASE (Maximum Likelihood Adaptive Subspace Estimation) is first analysed to address the problem of adaptive estimating the subspace of the data covariance matrix. Then, with the combination of the above subspace tracking algorithm with the Mini-norm high resolution algorithm, and using the Zero-tracking technology, an adaptive Mini-norm algorithm is proposed to track the time-varying DOAs (directions of arrival). Computer simulation results are provided to demonstrate the effectiveness of the proposed algorithm. |
| DOI：10.11684/j.issn.1000-310X.2005.05.012 |
| 中文关键词: 自适应子空间估计 DOA跟踪 MALASE 零点跟踪 |
| 英文关键词: Adaptive subspace estimation DOA tracking MALASE Zero-tracking |
| 基金项目: |
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