摘要
针对常规逆波束形成(IBF)算法存在旁瓣较高和分辨力无法突破瑞利限等固有缺陷,提出了一种基于自回归(AR)模型的改进的IBF求解方法。该方法通过对阵元域数据的AR建模,将参数模型引入到IBF积分方程的求解中,可以更充分的将各阵元接收信号的信息利用到声场的空间谱估计中,从而大大提高常规的傅里叶类IBF算法的分辨性能;并通过对互谱矩阵空间分布的滑动平均处理,改善了旁瓣起伏,有利于实现对弱目标信号的检测与估计;该方法无需对信源数进行预估,在低信噪比下亦有稳健的性能。大量计算机仿真实验从不同角度对本文方法的性能进行了考证,湖试数据的处理结果进一步证实了本文算法的可行性和优越性。
Aimed at some inherent shortcomings,such as high sidelobe level and limited resolution,of common inverse beam-forming(IBF),a new solution for the IBF integral equation based on an auto-regressive(AR) model is presented.By regarding the received data of each element as a spatial sequence satisfying a certain AR model,the method introduces the parametric model into the solution of the IBF integral equation and makes full use of the information received by the array to estimate the spatial spectrum of the acoustic field.The method also uses the sliding average to suppress the sidelobe,and it is beneficial to the DOA estimation for the weak target signal.The pre-estimate for number of source is not required,which makes it has a robust performance than the high resolution methods based on subspace decomposition in low SNR.The feasibility and superiority of the method are confirmed by the numerical simulations and the lake experiment results.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2011年第3期309-314,共6页
Acta Armamentarii
基金
第42批中国博士后科学基金一等资助(20070420181)
首批中国博士后科学基金特别资助(200801487)
关键词
声学
逆波束形成
傅里叶积分法
自回归模型
高分辨
稳健性
acoustics
inverse beamforming
Fourier integral method
auto-regressive model
high resolution
robustness