宽带盲波束形成与卷积混合盲源分离

盲波束形成是在不知道阵形，目标方位以及阵元响应等信息的情况下，只根据阵元输出恢复源信号。现有盲波束形成对窄带信号研究比较多。而对宽带信号盲波束形成论述较少。本文从信号模型，系统框图。处理的三方面说明盲波束形成与盲源分离近似，并指出卷积混合模型盲源分离完全可以作为解决宽带信号盲波束形成问题的一种通用方法。     

三种宽带自适应波束形成器比较研究

1引言 在被动声呐系统中,目标信号通常是宽带的,因此必须利用DFT将信号分解成若干个窄带,然后再每个窄带上利用MVDR波束形成技术.对于MVDR波束形成算法而言,是将宽带分为若干个窄带,在每个窄带上求出协方差矩阵,再把每个窄带的结果能量相加得到宽带结果,这就假定了各个窄带互不相关,所示是非相干累积,非相干累积要损失信息.事实上,各个窄带并非完全不相关,因此我们将研究针对宽带信号的相干波束形成或空间能量谱估计.     

一种利于工程应用的快速反卷积波束形成方法

针对传统的反卷积波束形成算法在处理宽带随机信号时计算量过大的问题,给出了一种利于工程应用的快速反卷积波束形成方法。利用不同频率阵列波束图的相似性,将宽带随机信号划分成非等间距的多个窄带,并在每个窄带取一个频率点的点扩散函数(Point Spread Function, PSF)进行反卷积的近似处理,极大地提高了反卷积波束形成的计算速度。通过在波束功率谱上进行边界扩展,解决了因 Richardson-Lucy(R-L)迭代算法带来的边界模糊问题,进一步提高了计算速度。仿真和海试结果表明,该方法相对于常规波束形成具有更高的分辨力、更高的处理增益和更好的旁瓣抑制能力;相对于传统反卷积波束形成计算速度提升了 50%以上。     

盲波束形成算法仿真及水下试验

盲波束形成技术是针对通信信号的统计性质和确定性性质所构成的一类新的波束形成技术.文中首先对高阶累积量法、基于累积量和特征空间的方法以及最陡下降恒模算法这三种盲波束形成算法进行了详细阐述,然后运用这些算法对单信号源均匀线阵、双信号源均匀线阵、单信号源随机扰动阵和双信号源随机扰动阵四种情况进行仿真.结果表明,三种算法可以进行有效的波束形成,基于累积量和特征空间的方法具有最高的输出信噪比.此外,还通过处理实际水下试验数据验证了这三种算法在实际应用中的有效性.     

强干扰背景下的鱼雷辐射噪声信号检测方法

常规被动声纳利用宽带波束能量进行目标检测,在低信噪比、强目标干扰情况下,宽带能量检测的性能迅速降低。利用鱼雷辐射噪声信号中含有丰富线谱成分的特点,提出了一种针对鱼雷辐射噪声信号的窄带和宽带联合检测方法。通过对预成波束方向信号的窄带处理和线谱提取,利用特定频段的线谱能量对宽带波束输出进行加权,提高了线谱目标的检测能力。该方法能够有效地抑制非线谱强干扰目标,提高低信噪比信号的检测能力。仿真和海试数据处理结果验证了该方法的有效性。     

SAVSTMV波束形成算法研究

矢量阵常规波束形成(Vector array Conventional Beam Forming,VCBF)能够消除普通单线阵左右舷模糊现象,但VCBF波束宽度受到"瑞利限"的限制,不能分辨同一波束内的多个目标。矢量阵导向最小方差(Vector array STeered Minimum Variance,VSTMV)波束形成算法是一种宽带自适应波束形成算法,具有高分辨力和抗干扰性能。VSTMV波束形成直接在阵元域进行,计算量较大且稳健性差,不利于实时实现和应用。提出一种分子阵VSTMV波束形成算法(Sub-Array Vector array Steered Minimum Variance,SAVSTMV),可有效降低计算量,算法稳健性更强。通过理论研究和仿真计算,证明该算法比矢量阵常规波束形成算法具有更好的性能,有利于实际应用。     

自适应Notch滤波器在阵列信号处理中的应用

为了不增大阵列尺度采用信号处理方法得到高分辨率的波束指向性,首先利用Notch滤波器的＂离线重构＂实现窄带波束形成,进而结合其瞬时相位估计方法,研究了基于自适应Notch滤波器的恒定束宽波束形成技术,利用信号处理方法将矢量传感器阵列接收的低频窄带信号转化为具有指向性的较高频率波束,并采用虚拟阵元技术消除波束栅瓣的影响,给出了实际应用中具体的信号处理方法。仿真和湖试验证表明这种基于自适应Notch滤波器的恒定束宽波束形成方法是合理可行的。最后,针对适应实时信号处理的要求提出将这种方法与目标自动跟踪系统相结合的改进方向。     

盲波束形成算法及其C语言实现

阵列信号处理作为信号处理的一个重要分支，在通信，雷达，声呐，地震勘探，射电天文等领域获得了广泛应用和迅速发展。波束形成技术是阵列信号处理中的一个主要问题，它使阵列方向图的主瓣指向所需的方向，盲波束形成算法，可以在不知道阵列流形，信号和干扰方位的情况下，仅根据各个阵元的观测数据，恢复出信号．本文主要讨论应用VC 语言实现和比较了几种基于累积量的盲波束形成算法的性能。     

基于波束域相干信号子空间法的宽带源小尺度基阵定向

在给定的小尺度平面四元阵的基础上,主要研究了波束域相关信号子空间算法(BeamSpaceCoherentSignal-subspaceMethod—BSCSM)在宽带源定向中的应用以及性能分析。用实测的直升机噪声仿真产生各个阵元上输出的宽带信号源,并且使得这组信号具有特定的波达方向(DirectionofArrival—DOA)。分别使用波束域相干信号子空间法(BSCSM)和阵元域的相干信号子空间法(CoherentSignal-subspaceMethod—CSM)与非相干信号子空间法(InCoherentSignal-subspaceMethod—ICSM),通过计算机仿真实验对其进行方位估计。在仿真实验中,可以直观地看出三种方法的性能优劣。根据计算机仿真结果,统计意义上的误差分析,以及对宽带平面波波达角度的角度分辨率等性能指标的分析比较,可以得出在小尺度基阵定向研究中,波束域方法能够获得比其他两种阵元域算法更好的性能。     

线列阵多倍频程宽频带恒定束宽的实现

利用N+1个嵌套线列阵在工程上实现了N个倍频程恒定束宽的波束形成.各个嵌套阵用切比雪夫加权,第I个倍频程对应的长短阵的输出信号分别通过数字低高通补偿滤波器相加后再通过第I倍频程椭圆带通滤波器,最后把N个带通滤波器的输出信号相加,则获得宽带恒定束宽的波束输出信号.文章给出了N个嵌套线列阵的宽频带恒定束宽的方向性图.     

智能天线MC-CDMA系统中空频联合盲多用户检测算法

提出了智能天线多载波CDMA系统中一种空域和频域联合的盲多用户自适应检测算法,它是将空域波束形成和频域合并检测合二为一,使得检测器在空域和频域两维上同时优化,从而提高了系统的检测性能.对这种空频联合检测算法的误码性能进行了分析,并与先自适应波束形成然后再进行频域合并的分步算法进行了仿真比较,仿真结果表明,提出的空频联合盲多用户自适应检测算法的检测性能优于分步检测算法.     

故障滚动轴承振动信号的半盲处理方法研究

利用旋转机械的振动信号的循环平稳特性,采用基于二阶统计量（Second Order Statistic,SOS）的盲均衡技术从多个传感器信号中恢复出“真实的”振动源信号,实现了同类信号的数据级融合。以滚动轴承故障信号的阶次谱结构为先验知识,提出了用于滤波性能评价的两个指标,实现了盲均衡滤波器参数的优化,从而给出了一种可用于滚动轴承故障诊断的半盲信号处理方法。采用某型单级减速齿轮箱的实验数据验证了该方法的有效性。     

用慢特征分析算法实现水声信号盲分离

在常规的水声信号盲处理研究中,通常都是用独立成分分析算法分离线性混合信号,而对于较复杂的非线性混合信号,独立成分分析算法无能为力。针对这种情况,提出将慢特征分析(Slow Feature Analysis,SFA)算法应用于水声信号非线性盲源分离领域。一般而言,对源信号做非线性混合变换后输出混合信号较源信号变化较快,而采用SFA算法可以从复杂的非线性混合信号中提取出变化缓慢的信号,通过仿真实验,分别对简单信号和复杂水声信号的非线性混合信号进行分离,通过将源信号与分离信号对比,发现SFA算法输出信号与源信号高度相似,验证了SFA算法在非线性盲源分离领域应用的有效性和可行性。     

基于时域波束信号高阶谱的目标检测技术

为解决常规时域波束形成技术抗噪声能力弱、对弱目标检测能力差的问题,利用高斯噪声的高阶累积量(三阶及三阶以上)为零、非高斯信号的高阶累积量不为零这一性质,对常规时域波束形成后输出的波束信号进行后置处理。首先,对常规时域波束形成后输出的各预成波束信号,分别求其四阶累积量切片谱值;然后,再对各四阶累积量切片谱值分别进行能量累加,得到空间谱图;最后,通过对空间谱在时间上的累积,得到方位历程图。用仿真和海试数据对算法进行了验证:在低信噪比情况下,常规算法不能有效检测到弱目标时,经后置处理后可以有效检测到弱目标。结果表明,与常规时域波束形成算法相比,波束形成后再进行切片谱后置处理的算法增强了对噪声的抑制能力,提高了对弱目标的检测能力。     

Performance Analysis of Relay Based NOMA Cooperative Transmission under Cognitive Radio Network

This paper proposes a hybrid spectrum accessing mechanism by using NOMA-based cooperative transmission and beam-forming technology. In this mechanism, the secondary user employs spectrum-sensing technology to detect the existence of the primary user. If the primary user does not exist, the secondary source user directly transmits data to the destination user. If the primary user exists, the secondary source user finds the optimal relay according to certain selection principle before transmitting data to the destination user through the chosen relay node. For the signal receiving stage, the secondary user takes use of beam-forming technology to receive the signal from both the secondary source and the secondary relay node. Meanwhile the interference from the primary user is cancelled out in the stage. Furthermore, the outage probability for secondary user in the proposed mechanism is theoretically derived. Finally, the simulation results show that compared with the traditional mechanism, the proposed system model can not only guarantee the continuity of secondary transmission, but also significantly reduce the outage probability of secondary transmission.     

Image reconstruction for photoacoustic scanning of tissue structures

Photoacoustic signal generation can be used for a new medical tomographic technique. This makes it possible to image optically different structures, such as the (micro)vascular system in tissues, by use of a transducer array for the detection of laser-generated wide-bandwidth ultrasound. A time-domain delay-and-sum focused beam-forming technique is used to locate the photoacoustic sources in the sample. To characterize the transducer response, simulations have been performed for a wide variety of parameter values and have been verified experimentally. With these data the weight factors for the spectrally and temporally filtered sensor signals are determined in order to optimize the signal-to-noise ratio of the beam former. The imaging algorithm is investigated by simulations and experiments. With this algorithm, for what is to our knowledge the first time, the three-dimensional photoacoustic imaging of complex optically absorbing structures located in a highly diffuse medium is demonstrated. When 200-mum-diameter hydrophone elements are used, the depth resolution is better than 20 mum, and the lateral resolution is better than 200 mum, independent of the depth for our range of imaging (to ~6 mm). Reduction of the transducer diameters and adaptation of the weight factors, at the cost of some increase of the noise level, will further improve the lateral resolution. The synthetic aperture algorithm used has been shown to be suitable for the new technique of photoacoustic tissue scanning.     

Approach to blind image deconvolution by multiscale subband decomposition and independent component analysis

A single-frame multichannel blind image deconvolution technique has been formulated recently as a blind source separation problem solved by independent component analysis (ICA). The attractive feature of this approach is that neither origin nor size of the spatially invariant blurring kernel has to be known. To enhance the statistical independence among the hidden variables, we employ multiscale analysis implemented by wavelet packets and use mutual information to locate a subband with the least dependent components, where the basis matrix is learned by means of standard ICA. We show that the proposed algorithm is capable of performing blind deconvolution of nonstationary signals that are not independent and identically distributed processes. The image poses these properties. The algorithm is tested on experimental data and compared with state-of-the-art single-frame blind image deconvolution algorithms. Our good experimental results demonstrate the viability of the proposed concept.     

Sparse Deconvolution Methods for Ultrasonic NDT

In this work we present two sparse deconvolution methods for nondestructive testing. The first method is a special matching pursuit (MP) algorithm in order to deconvolve the mixed data (signal and noise), and thus to remove the unwanted noise. The second method is based on the approximate Prony method (APM). Both methods employ the sparsity assumption about the measured ultrasonic signal as prior knowledge. The MP algorithm is used to derive a sparse representation of the measured data by a deconvolution and subtraction scheme. An orthogonal variant of the algorithm (OMP) is presented as well. The APM technique also relies on the assumption that the desired signals are sparse linear combinations of (reflections of) the transmitted pulse. For blind deconvolution, where the transducer impulse response is unknown, we offer a general Gaussian echo model whose parameters can be iteratively adjusted to the real measurements. Several test results show that the methods work well even for high noise levels. Further, an outlook for possible applications of these deconvolution methods is given.     

阵元信号相幅非一致性对波束形成的影响

在波束形成技术中,由于各输入通道相幅的不一致性和阵元位置的误差,而将影响波束形成性能.本文以小型舷侧阵为研究对象,首先介绍了含有误差分量的波束模型,并推导了含有误差分量的波束输出能量模型.然后分别从阵元的相位误差、幅度误差和位置误差三个方面着手,理论分析和计算机仿真相结合,详细介绍了它们对波束形成的影响,对工程应用具有现实的指导意义.