闪电通道重构的时间反转和多重信号分类技术

近年来,连续宽带阵列信号处理算法在闪电甚高频(VHF)定位领域取得一系列突破性进展,展现出相对于传统广义互相关闪电定位算法的明显优势,可实现对闪电通道高精度、高分辨反演重建,促进对闪电小尺度精细特征的科学研究。文章梳理了宽带甚高频阵列技术在闪电辐射源定位领域的国内外研究进展和应用情况,详细阐述了宽带甚高频阵列时间反转(TR)和多重信号分类(MUSIC)算法的原理和实现步骤,对比分析了两种算法的定位精度、空间分辨率以及抗干扰能力。针对实际观测应用中面临的问题,对一些可能的研究方向进行了展望,供广大研究人员参考借鉴。     

多普勒效应对雷电源辐射定位的影响关系研究

定位过程中考虑雷电辐射源运动所产生的多普勒效应这一因素，有助于提高定位结果的准确程度. 基于电磁波多普勒效应和阵列信号的波束形成算法，本文建立了多普勒效应对接收信号和雷电辐射源定位的数学模型，研究了雷电源的运动速度、运动方向对定位结果的影响，总结了多普勒效应对定位结果产生影响的变化关系. 仿真结果表明:当雷电发展速度增加时，接收频率误差随之增加，尤其雷电源运动速度在107～108 m/s（箭式先导和回击阶段）产生的频率误差值呈现激增的趋势, 其相对误差在20%左右，雷电源辐射定位的准确度也急剧下降；雷电源运动方向与来波方向夹角α在180°～360°时接收频率误差的变化为先减小后增大，雷电源辐射定位的准确度有不同程度的下降. 该研究可为雷电精细化研究提供依据.     

一种基于SPWVD-WVD的高质量时频分析方法及ISAR成像应用

交叉项干扰抑制与高时频聚集度是准确反应信号的时频分布特征的重要因素。传统的魏格纳-维尔分布(Wigner-Ville Distribution,WVD)算法虽能获得较高的时频分辨特征,但分析多成分信号时存在严重的交叉项干扰问题,限制了其实用性;而平滑伪魏格纳-维尔分布(Smoothed Pseudo Wigner-Ville Distribution,SPWVD)算法虽在一定程度上抑制交叉项干扰,但降低了时频聚集度。为了解决上述问题,提出了基于SPWVD-WVD的时频分析方法。该方法利用SPWVD与WVD之间的滤波互消效应,将SPWVD二值化结果与WVD结果进行矩阵运算,最终得到高质量的时频分析结果。实验结果表明,所提出的算法能够有效去除多分量信号的交叉项干扰,提高信号分析结果的时频聚集度,还原多分量信号的真实时频分布。最后将该算法成功应用于逆合成孔径雷达成像中。     

基于互Wigner-Ville分布的到达角估计

研究了对线性调频信号的到达角估计;提出了基于互Wigner-Ville分布(XWVD)估计信号到达角的方法.通过时频分布,在时频面上进行信号预分选;根据XWVD时频脊点上的相位获得信号时延,从而获得信号到达角.该算法可实现多信号分辨,也可实现对时变频率信号的到达角估计.计算机仿真结果证实了该算法的有效性.     

时频分析:回溯与前瞻

时频分析旨在构造一种时间和频率的密度函数,以揭示信号中所包含的频率分量及其演化特性.本文以抑制Wigner-Ville分布中的交叉项干扰为主线,综述了时频分析的历史沿革、面临的挑战,及在一些领域中的应用.     

时频空域混叠脉冲串辐射源信号直接定位算法

当既定侦察区域存在多个数目未知且信号参数相似的脉冲串辐射源信号时,采用经典的多目标定位算法和直接定位算法(DPD)均无法对多个辐射源信号进行精确定位.该文提出了一种基于位置信息累积的脉冲串直接定位算法(L-DPD).算法采用多个运动侦察站对固定目标辐射源进行信号接收,充分利用脉冲串信号的位置信息并联合各脉冲的时延、频移...     

线性调频信号辐射源的唯方位跟踪

对宽带线性调频信号的方位角估计以及对这类信号辐射源单站跟踪问题进行了研究.算法通过对称阵元Wigner-Ville分布(WVD),建立了一种新颖的具有分维结构的空间时频分布数据模型,并利用Beamspace-ESPRIT和子空间投影法估计信号瞬时频率向量和到达角.在到达角估计的基础上,针对在直角坐标系中利用扩展的卡尔曼滤波器的唯方位跟踪法不稳定问题,采用了修改的极坐标,实现了运动单站对运动辐射源的稳定和渐进无偏的定位与跟踪.     

时频面滑窗掩膜的多分量信号高效重构算法

针对基于特征值分解的 Wigner-Ville 分布信号重构算法运算复杂度高这一问题,该文提出一种高效多分量信号重构算法。首先,通过分析 Wigner-Ville 逆变换公式,推导出瞬时时刻重构序列与原序列之间的联系,提出一种高效的信号重构算法。然后,采用平滑伪Wigner-Ville分布作为时频掩膜抑制Wigner-Ville分布的交叉项,并通过在时频面内滑窗的方法逐一提取各分量信号。最后,结合高效信号重构算法和时频面滑窗掩膜技术,实现多分量信号快速准确重构。仿真实验证明了该算法的有效性和可行性。     

基于时频子空间分解的宽带线性调频信号DOA估计

针对具有时变方向向量的宽带线性调频信号,该文建立了基于短时Wigner-Ville分布(WVD)的空间时频分布矩阵,通过对各个空间时频矩阵的特征分解获得对应的信号子空间和噪声子空间,给出了基于时频子空间投影实现多个时频点综合估计信号DOA的算法。利用空间时频分布的前后向平滑解决了具有相同时频特性信号的均匀线阵DOA估计问题。算法不需要聚汇和插值等复杂的矩阵变换,精度较高,计算简便.仿真实验显示该算法性能显著优越于基于矩阵插值的宽带调频信号DOA估计算法.     

基于广义矩形时频分布的跳频信号参数估计

能够有效地对接收到的跳频信号进行参数估计是干扰跳频通信的重要前提。由于广义矩形时频分布能够在有效抑制交叉干扰项的同时具有好的时频聚集性,提出了一种基于广义矩形时频分布的跳频信号参数盲估计算法。该算法能够在低信噪比条件下估计出跳频信号的跳频周期、跳变时刻和跳频频率。仿真结果表明,与基于平滑伪Wigner-Ville时频分布（SPWVD）估计跳频信号参数的算法进行比较,该算法提高了跳频信号参数估计的准确度和可靠性。     

利用空间时频分布实现宽带FM信号2-D到达角估计

提出了一种新的宽带FM信号二维到达角估计方法。本算法将L型天一阵两个臂的空间时频分布矩阵分别进行相干信号子空间平滑处理，并用子窨 方法实现方位和俯仰角估计，计算机仿真证实了算法的有效性。     

Near-field time-frequency localization method using sparse representation

This paper presents a novel near-field source localization method based on the time-frequency sparse model.Firstly,the method converts the time domain data of array output into time-frequency domain by time-frequency transform;then constructs sparse localization model by utilizing the specially selected time-frequency points,and finally the greedy algorithms are chosen to solve the sparse problem to localize the source.When the coherent sources exist,we propose an additional iterative selection procedure to improve the estimation performance.The proposed method is suitable for uncorrelated and coherent sources,moreover,the improved estimation accuracy and the robustness to low signal to noise ratio(SNR) are achieved.Simulations results verify the efficiency of the proposed algorithm.     

基于集成固有时间尺度分解的IFF辐射源个体识别算法

为研究敌我识别(IFF)辐射源信号的细微特征,针对目前在复杂噪声环境中IFF辐射源个体识别研究不足的问题,该文提出一种基于集成固有时间尺度分解的IFF辐射源个体识别算法。该算法应用集成固有时间尺度分解(EITD)将采样信号自适应划分为若干有实际意义的信号分量并求取IFF辐射源信号在时频域的能量分布图。通过对时频能量谱的纹理分析,以图像的纹理特征表征辐射源信号的无意调制特征,送入支持向量机(SVM)中进行分类识别。实验表明,所提算法相较于基于希尔伯特-黄变换(HHT)、基于固有时间尺度分解(ITD)的辐射源个体识别方法在识别准确度上有较大提升。     

Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks

A maximum likelihood (ML) acoustic source location estimation method is presented for the application in a wireless ad hoc sensor network. This method uses acoustic signal energy measurements taken at individual sensors of an ad hoc wireless sensor network to estimate the locations of multiple acoustic sources. Compared to the existing acoustic energy based source localization methods, this proposed ML method delivers more accurate results and offers the enhanced capability of multiple source localization. A multiresolution search algorithm and an expectation-maximization (EM) like iterative algorithm are proposed to expedite the computation of source locations. The Crame/spl acute/r-Rao Bound (CRB) of the ML source location estimate has been derived. The CRB is used to analyze the impacts of sensor placement to the accuracy of location estimates for single target scenario. Extensive simulations have been conducted. It is observed that the proposed ML method consistently outperforms existing acoustic energy based source localization methods. An example applying this method to track military vehicles using real world experiment data also demonstrates the performance advantage of this proposed method over a previously proposed acoustic energy source localization method.     

Spatial averaging of time-frequency distributions for signalrecovery in uniform linear arrays

This paper presents a new approach based on spatial time-frequency averaging for separating signals received by a uniform linear antenna array. In this approach, spatial averaging of the time-frequency distributions (TFDs) of the sensor data is performed at multiple time-frequency points. This averaging restores the diagonal structure of the source TFD matrix necessary for source separation. With spatial averaging, cross-terms move from their off-diagonal positions in the source TFD matrix to become part of the matrix diagonal entries. It is shown that the proposed approach yields improved performance over the case when no spatial averaging is performed. Further, we demonstrate that in the context of source separation, the spatially averaged Wigner-Ville distribution outperforms the combined spatial-time-frequency averaged distributions, such as the one obtained by using the Choi-Williams (1989) distribution. Simulation examples involving the separation of two sources with close AM and FM modulations are presented     

雷电辐射源定位的时间反转方法与应用

将频域时间反转（time reversal，TR）聚焦技术应用于雷电辐射源探测定位，介绍了雷电辐射源探测系统的基本组成和TR定位算法，讨论了定位精度的影响因素，给出了典型应用实例.通过与传统的方法进行对比，发现该方法具有较好的鲁棒性，无需提取波形的到达时刻等信息，可直接利用检测波形的反向传播进行自动聚焦定位，并具有多辐射源同时定位的潜力.     

Broadband source tracking using adaptive directional filter withmaximally flat responses at null directions

A new algorithm for the tracking of broadband sources in linear arrays employing tapped delay line processing is presented and investigated. Using this technique, each broadband source is individually tracked in a time-multiplexed manner by steering a broadband null formed from the use of a tapped delay line filter whose weights are constrained to have a maximally flat frequency response at the nulling direction. To ensure that the other nulls are not changed while a particular null is being adjusted, a beamformer is employed to preprocess the element signals before adaptive processing. Since the new algorithm updates only one tapped delay line filter at any instant, the overall implementation complexity of the proposed algorithm is comparable with using the LMS algorithm directly on a broadband array. However, unlike the latter algorithm, the convergence behavior of the new algorithm is significantly faster and is almost independent of the external noise environment     

宽带高速跳频信号的精细化侦察处理技术研究

当空间中存在大带宽、频率快速跳变的辐射信号时，传统侦察接收机无法实现完整接收与准确识别。针对上述问题，提出一种宽带精细化侦察处理方法，实现了宽带实时数据采集与精细化时频分析，获得了多部辐射源信号特征参数的准确分类，并且生成了完整的辐射源态势信息与有效的敌方行为预测结果。实验结果表明，该方法能够实现宽带高速跳频信号的全概率接收及精确解析测量。     

Fractional delay estimation for blind source separation and localization of temporomandibular joint sounds

Temporomandibular joint (TMJ) sound sources are generated from the two joints connecting the lower jaw to the temporal bone. Such sounds are important diagnostic signs in patients suffering from temporomandibular disorder (TMD). In this study, we address the problem of source separation of the TMJ sounds. In particular, we examine patients with only one TMJ generating "clicks". Thereafter, we consider the TMJ sounds recorded from the two auditory canals as mixtures of clicks from the TMD joint and the noise produced by the other healthy/normal TMJ. We next exploit the statistical nonstationary nature of the TMJ signals by employing the degenerate unmixing estimation technique (DUET) algorithm, a time-frequency (T-F) approach to separate the sources. As the DUET algorithm requires the sensors to be closely spaced, which is not satisfied by our recording setup, we have to estimate the delay between the recorded TMJ sounds to perform an alignment of the mixtures. Thus, the proposed extension of DUET enables an essentially arbitrary separation of the sensors. It is also shown that DUET outperforms the convolutive Infomax algorithm in this particular TMJ source separation scenario. The spectra of both separated TMJ sources with our method are comparable to those available in existing literature. Examination of both spectra suggests that the click source has a better audible prominence than the healthy TMJ source. Furthermore, we address the problem of source localization. This can be achieved automatically by detecting the sign of our proposed mutual information estimator which exhibits a maximum at the delay between the two mixtures. As a result, the localized separated TMJ sources can be of great clinical value to dental specialists.