摘要
构造了一种特殊的阵列结构,定义了子阵列输出信号之间的互协变异矩阵,提出了一种在SαS噪声环境中基于分数低阶矩的二维子空间测向算法。该算法利用SαS过程具有p(p≥α)阶矩无限、而分数p(0≤p<α)阶矩有限等特点,扩展了二维测向算法的信号模型和应用环境,对加性SαS噪声有较好的抑制作用,弥补了传统的基于二阶和高阶统计量的子空间测向算法不能应用于冲击噪声环境的不足。计算机仿真验证了该算法的可行性和有效性。
Constructs a particular array geometric configuration, and defines the cross-covariation matrix of the sub-array sensor outputs. Final, a subspace-based 2-D bearing estimation algorithm using fractional lower order statistics is proposed in the presence of impulsive noise which can be modeled as a complex symmetric alpha-stable (SaS) process. The method extends signal models and application situation of 2-D direction finding algorithm by exploiting the infinite pth-moments for p > a and finite fractional pth-order moments only for 0 < p < a for SaS processes. The algorithm is robust against additive SaS noise, which remedies the lack of the traditional subspace-based techniques employing both second-order or higher order moments cannot be applied in impulsive noise environments. The simulation results show the feasibility and effectiveness of the algorithm.
出处
《声学学报》
EI
CSCD
北大核心
2004年第2期149-154,共6页
Acta Acustica
基金
国防预研基金(00033)
