摘要
信源的到达角(Direction of Arrive,DOA)信息在许多实际应用领域中具有重要作用,因此对DOA的准确估计是阵列信号处理领域的研究热点。针对传统信号子空间非相干处理方法(Incoherent Signals-subspace Method,ISM)在含有混响的低信噪比环境下对宽带信号进行DOA估计时存在的准确性低的问题,文中提出一种基于ISM算法的改进算法。该算法首先利用离散傅里叶变换将宽带信号分解为若干子频带;其次提出一种构建能量门限的方式,通过该能量门限筛选子频带并保留能量高于该门限的子频带;然后提出一种协方差矩阵重构方法,重构每一个子频带的协方差矩阵,通过TLS-ESPRIT算法估计每一个子频带的DOA参数;最后提出一种加权策略对多个子频带的DOA估计值进行处理,得到最终的DOA估计值。实验结果表明,该算法可以有效地提高宽带信号DOA的准确性,并且具有较好的鲁棒性。
The Direction of Arrive(DOA)information of the source plays an important role in many practical applications.Therefore,it is a research hotspot to estimate the DOA accurately in the field of array signal processing.In view of the low accuracy of the traditional ISM(Incoherent Signals-subspace Method)for DOA estimation of broadband signals in a low SNR and reverberation condition,this paper presented an improved DOA estimation algorithm based on the ISM.Firstly,the wideband signal is decomposed into several sub-bands by discrete Fourier transform.Secondly,a way to construct an energy threshold is proposed by which the sub-band is filtered by the energy threshold and the sub-band with energy above the threshold is reserved.Thirdly,a covariance matrix reconstruction method is used to reconstruct the covariance matrix of each sub-band,and the DOA parameters of each sub-band are estimated by the TLS-ESPRIT algorithm.Finally,a weighting strategy is proposed to process the DOA estimates of multiple sub-bands and the final DOA is estimate accurately.The experimental results show that the proposed algorithm can effectively improve the accuracy of broadband signal DOA and has better robustness.
作者
徐正勤
伍世虔
刘清宇
XU Zheng-qin;WU Shi-qian;LIU Qing-yu(Hubei Collaborative Innovation Center for Advanced Steels,Wuhan University of Science and Technology,Wuhan 430081,China;School of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《计算机科学》
CSCD
北大核心
2019年第S11期376-380,398,共6页
Computer Science
基金
国家自然科学基金项目(51805381)资助
关键词
DOA估计
ISM
宽带信号
能量门限
能量加权
重构协方差矩阵
Direction of arrival estimate
Incoherent signals-subspace method
Broadband signal
Energy threshold
Energy weighted
Reconstruct the covariance matrix