主动自导水下航行器的高分辨宽带信号检测技术

为了提高主动自导水下航行器对目标的识别能力,提出一种基于自小波变换的主动自导水下航行器的高分辨宽带信号检测技术,构建主动自导水下航行器的回波信号模型,在海水混响干扰下采用自相关匹配滤波器进行信号滤波处理,对滤波输出的宽带信号采用自小波变换进行时频分解,对水下航行器的回波探测信号作WVD-Hough变换,采用二维谱峰搜索方法实现高分辨的目标信号检测。仿真结果表明,采用该方法进行主动自导水下航行器的宽带信号检测的准确检测概率较高,抗旁瓣干扰能力较强,对打击目标的具有高分辨识别能力。     

基于FRFT的频域自适应匹配滤波器检测方法

针对浅海混响背景下频域自适应匹配滤波器检测性能下降的问题,提出基于分数阶傅里叶变换（FRFT）的频域自适应匹配滤波器检测方法,该方法利用模板匹配技术,采用滑动窗对接收信号进行最优阶次分数阶傅里叶变换,然后将此过程中得到的FRFT域图与参考信号最优阶次傅里叶变换FRFT域图进行匹配,将离差平方和作为评价相似度的指标,即对离差平方和最小值的位置进行滤波,并对滤波后的信号进行最优阶次分数阶傅里叶逆变换,从而实现混响背景下的目标检测。仿真结果表明,在信混比为-15 dB的情况下,该算法可显著提高频域自适应匹配滤波器的检测性能。     

云计算船舶通信网络的入侵特征提取与检测

船舶通信网络入侵特征具有宽带严平稳性,导致在入侵检测中容易受到小扰动影响,检测性能不好,在云计算环境下,提出基于时间尺度分解和谱密度特征提取的船舶通信网络的入侵特征提取与检测方法。构建云计算船舶通信网络入侵信息流检测模型,采用时频分析方法进行入侵特征的时延尺度分析,结合匹配滤波方法进行船舶通信网络的干扰滤波,对滤波后的网络传输信号进行谱分析,提取谱密度特征,根据谱密度分布的差异性实现对入侵特征提取和信号检测。仿真结果表明,采用该方法进行云计算船舶通信网络入侵检测的准确概率较高,保障了网络安全。     

基于小波框架与匹配追踪算法的宽带回波信号处理

文章主要研究如何基于小波框架与匹配追踪算法处理宽带回波信号,以求得运动目标的速度与位置。通过对宽带回波模型的研究,可以发现宽带回波信号的表示形式与小波框架存在一定的相似性。因此文章尝试将宽带回波信号用由发射信号生成的小波框架来表示,然后通过匹配追踪算法设法将时延-时间伸缩联合分布密度函数D(s,τ)求出,最终得到运动目标的速度与位置。通过仿真发现文中提出的算法取得了较好的效果,这对今后研究宽带回波信号的处理具有一定的指导意义。     

多路水声信号抗串漏检测技术仿真

根据水下多目标定位系统水声通道特点和系统海上试验实际应用情况,建立系统多路合作水声信号检测处理仿真模型。仿真表明:采用FIR宽带滤波器、Notch滤波器组和瞬时频率方差序列等水声信号处理技术,能有效克服系统水声通道串漏、高斯白噪声和鱼雷寻的噪声对信号检测的影响,实现系统对多路合作水声信号的检测处理。     

基于chirplet的匹配追踪在超声导波信号处理中的应用

使用基于chirplet时频原子的匹配追踪方法,对超声导波管道检测信号进行分析处理,并与基于Gabor时频原子的处理结果进行了比较。研究结果表明,chirplet时频原子能反映出的超声导波检测信号的频率变化特征,得到的时频分布与频散曲线能很好的吻合,基于chirplet原子的匹配追踪方法更适合于超声导波检测信号处理。     

一种级联型自适应滤波器的混响抑制技术

在浅海环境中混响是造成主动声呐性能下降的主要原因之一。混响是由发射信号引起的,其频域上覆盖区域与发射信号基本重合,时域上与发射信号及目标回波强相关,这给混响和目标的分离造成了很大的困难。本文借鉴PD雷达中的动目标检测方法,提出一种适用于声呐动目标检测的滤波器设计算法。该算法利用运动目标回波和混响在时频域上的不同特性,设计了级联自适应滤波器实现混响抑制和目标增强。在此基础上进行匹配滤波等处理可以获得理想的效果。该算法可大幅提高信混比,有效改善运动目标的检测能力。     

一种级联型自适应滤波器的混响抑制技术

在浅海环境中混响是造成主动声呐性能下降的主要原因之一。混响是由发射信号引起的,其频域上覆盖区域与发射信号基本重合,时域上与发射信号及目标回波强相关,这给混响和目标的分离造成了很大的困难。本文借鉴PD雷达中的动目标检测方法,提出一种适用于声呐动目标检测的滤波器设计算法。该算法利用运动目标回波和混响在时频域上的不同特性,设计了级联自适应滤波器实现混响抑制和目标增强。在此基础上进行匹配滤波等处理可以获得理想的效果。该算法可大幅提高信混比,有效改善运动目标的检测能力。     

磁性天线数字化全向图合成方案设计*

为了解决磁天线接收信号存在盲区的问题,提出一种可以用希尔伯特滤波器来完成的宽带甚低频水下通信全向接收新方法,完成数字化全向接收的理论推导。在未知信号载波频率的条件下,可实现对信号进行宽带移向,从而完成磁性天线数字化全向合成。仿真结果表明,设计方案合理可行,可用于宽频带信号全向天线的数字化合成。     

基于频域搜索的梳状谱信号检测方法

由于梳状谱信号多普勒容限较小,利用常规的匹配/相关检测方法进行检测时,需要较大数量的拷贝信号与计算量。针对这一问题,本文提出一种基于频域搜索的梳状谱信号检测算法。通过利用梳状谱信号频域多峰结构的特点,根据信号的先验信息计算出不同径向速度下回波信号的频点分布,对接收的信号在频域进行搜索累计的方法同时实现信号的检测与速度估计。仿真分析证明了本文算法的有效性。     

一种强干扰背景下雷达目标检测算法

将WVD和Hough变换相结合,利用时频聚集性和Hough变换点的累积得到的信号的检测结果,用来检测雷达目标回波信号。然而在强干扰低信噪比下检测能力有限。利用线性调频信号瞬时频率的线性特征,只采用信号WVD时间段的中间部分值进行Hough变换,在时频平面上对WVD的结果进行时间轴上的截取技术,对检测算法作了改进。通过仿真结果表明,改进的检测算法在低信噪比和强干扰环境下能有效地检测出目标信号。     

Blind source separation based on time–frequency morphological characteristics for rigid acoustic scattering by underwater objects

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time–frequency Blind Source Separation (BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time–frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner–Ville Distribution (WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. An experimental simulation has been used, with changes in the pulse width of the transmitted signal, the relative amplitude and the time delay parameter, in order to analyzing the feasibility of this new method. Simulation results show that the new method is not only able to separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.     

基于位置信息的宽带雷达目标距离段联合检测算法

宽带雷达目标回波表现为距离扩展目标的形式,距离扩展目标检测技术是目前雷达信号处理领域的一个热门和难点问题。文章通过对宽带雷达目标回波的分析,总结了回波的主要特性,详细介绍了采用基于距离窗信息的双门限检测器对宽带雷达信号进行检测的方法,提出了基于高分辨雷达目标一维距离像位置一径向距离相关信息的非参数检测方法。仿真结果表明,该方法不但计算复杂度低,而且还具有检测沿径向距离“走廊”上多个扩展目标的能力。     

基于先验信息的自适应核函数设计

针对多分量线性调频信号，提出一种新的自适应核函数，并给出了有效的核参数估计方法。相对于自适应高斯核函数而言，该核函数既能获得更好的交叉项抑制效果，又避免了较大的信号能量损失，因而是一种更好的核函数。计算机仿真结果验证了其有效性。     

基于WVD和Hough变换二值积累的信号检测方法

WVD-Hough变换是检测多分量线性调频信号的有力工具,但当多分量线性调频信号能量相差较大时,采用WVD-Hough变换进行检测,就会导致强信号对应峰值的平台将弱信号所对应的峰值掩盖掉。虽然可以通过基于＂CLEAN＂思想的算法将信号一一检测出来,但带来的计算量急剧增大。为此在WVD-Hough变换的基础上提出了基于WVD-Hough变换的二值积累方法,该方法可以同时检测出强信号以及被强信号平台掩盖的弱信号,具有很大的实用价值,仿真的结果验证了算法的有效性。     

船舶动力定位自适应滤波器设计

传统的陷波滤波器虽然能够很好的滤除一阶高频海浪波,但是滤波的同时也使得信号产生了相位滞后,在时域里面的表现就是信号的延时.卡尔曼滤波器虽然能够解决这一问题,但是其非常依赖于船舶模型.本文针对传统陷波滤波器的缺陷,使用了一种积分补偿型陷波滤波器,对传统的陷波滤波器进行改进.并以某拖轮为仿真对象进行仿真实验,其结果表明,该滤波器不但能够很好的滤除高频海浪波,还能够保持很好的相位特性.同时,递推的最小二乘估计(RLS)方法能够实时的估计出海浪的主导波频,使得陷波滤波器具有很好的自适应性.     

Instantaneous frequency estimation of multi-component Chirp signals in noisy environments

A classical time-varying signal,the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency(IF) is very useful. But in noisy environments,it is hard to estimate the IF of a multi-component Chirp signal accurately. Wigner distribution maxima(WDM) are usually utilized for this estimation. But in practice,estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal IF estimation named Wigner Viterbi fit(WVF) ,based on Wigner-Ville distribution(WVD) and the Viterbi algorithm. First,we transform the WVD of the Chirp signal into digital image,and apply the Viterbi algorithm to separate the components and estimate their IF. At last,we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments,and better suppression of interference and the edge effect. Compared with WDM,WVF can reduce the mean square error(MSE) by 50% when the signal to noise ration(SNR) is in the range of -15dB to -11dB. WVF is an effective and promising IF estimation method.     

水下目标几何声散射形态学特征的时频域盲分离（英文）

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time-frequency Blind Source Separation(BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time-frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner-Ville Distribution(WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. A simulation experimental has been used to analyze the feasibility of the new method, with changing the pulse width of the transmitted signal, the relative amplitude and the time delay parameter. And simulation results show that the new method can not only separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.     

一种通用型基于经验模态分解的小波阈值滤波方法研究

首先针对中高频水声信号,提出一种改进的经验模态分解加小波软阈值滤波方法;然后将信号进行带通滤波处理及经验模态分解,将分解得到的各个模态转换为频域信号,采用小波软阈值方法在频域上对这些模态进行滤波,最后对信号进行重构,并将其转换为时域信号。分别采用本方法和原时域上的小波阈值方法对不同频率的水声信号进行滤波,经计算分析可知,对频率小于800 Hz的水声信号,采用原方法可获得较好的滤波效果;当信号频率大于800 Hz时,采用本方法的滤波效果更好,因此应针对不同频率的水声信号,选择合适的滤波方法,以获得满意的滤波效果。     

Application of an improved EEMD method in bearing fault diagnosis of induction motors北大核心CSCD

[Objective]In order to overcome the disadvantages of the traditional ensemble empirical mode decomposition (EEMD) method in selecting parameters (integration time and white noise amplitude coefficient) based on experience, and reduce the cost of calculation time, a fast ensemble empirical mode decomposition (FEEMD) method is used to extract the characteristic frequency. [Method]By changing the distribution density of the added white noise, different signal envelopes can be obtained. Furthermore, we can identify the optimal envelope by finding the optimal search window width of the moving mean filter, thereby avoiding the defect of EEMD selecting parameters by experience. At the same time, after the abnormal component in the signal is decomposed, the residual component can be decomposed by EMD to further save the calculation time cost. Finally, the method is combined with Hilbert envelope demodulation technology and applied to the fault characteristic frequency diagnosis of the bearing inner ring of an asynchronous motor. [Results]As the results show, compared with the traditional EEMD method, FEEMD can extract the fault frequency more efficiently. [Conclusion]FEEMD overcomes the disadvantages of the traditional EEMD method in selecting parameters based on experience and shortens the calculation time. As such, it can be effectively applied in bearing fault frequency extraction experiments. © The Author(s) 2022.