摘要： 当信号中存在α稳定分布噪声时，传统空间时频多重信号分类(STF-MUSIC)算法的空间波达方向(DOA)估计性能会降低甚至失效。为此，利用分数低阶矩(FLOM)代替二阶协方差矩阵，定义分数低阶矩空间时频分布矩阵(FLOM-STFDM)。对FLOM-STFDM进行特征分解，得到适用于稳定分布噪声环境的空间时频TF-FLOM-MUSIC算法，分析该算法的信噪比及误差估计，并给出算法实现步骤。仿真结果表明，TF-FLOM-MUSIC算法可有效降低DOA估计的均方误差，提高估计的分辨率和平滑性。
关键词:
空间时频分布矩阵,
多重信号分类算法,
α稳定分布,
分数低阶统计量,
波达方向估计
Abstract: The performance of Direction of Arrival(DOA) estimation based on conventional Spatial Time-frequency Multiple Signal Classifi- cation(STF-MUSCI) degenerates in α stable distribution environment. A new Time-frequency Fractional Lower Order Moment MUSIC(TF- FLOM-MUSIC) method is proposed, second covariance matrix is substituted by Fractional Lower Order Matrix(FLOM) and Fractional Lower Order Moment Spatial Time-frequency Distribution Matrix(FLOM-STFDM) is defined, FLOM-STFDM is decomposed in the method. DOA estimation Mean Squared Error(MSE) and Generalized Signal Noise Ratio(GSNR) are analyzed and algorithm steps are summarized. Simulation results show that TF-FLOM- MUSIC algorithm can reduce effectively DOA estimation MSE and improve estimation resolution.
Key words:
Spatial Time-frequency Distribution Matrix(STFDM),
Multiple Signal Classification(MUSIC) algorithm,
α stable distribution,
Fractional Low Order Statistic(FLOS),
Direction of Arrival(DOA) estimation
中图分类号:
汪海滨, 查代奉, 龙俊波. α稳定分布噪声下的空间时频DOA估计[J]. 计算机工程, 2012, 38(2): 284-284.
HONG Hai-Bin, CHA Dai-Feng, LONG Dun-Bei. Spatial Time-frequency DOA Estimation Under α Stable Distribution Noise[J]. Computer Engineering, 2012, 38(2): 284-284.