快速ESPRIT谐波集检测算法

在各种高分辨谐波检测算法中,TLS-ESPRIT估计精度较高,因不需要谱峰搜索而具有较小的运算量。提出了一种快速ESPRIT算法,在不降低谱估计性能条件下,进一步减小了运算量。快速ESPRIT算法所需采样时间短,仅需两次特征值分解。分析表明,此算法可以检测不同飞行状态的直升机声信号谐波集,是一种实时性好、有效实用的目标谱集探测方法。     

行驶汽车环境中的话音活动检测研究

话音活动检测是语音交互和通信系统的重要部分,其作用是区分输入信号中的语音段和背景噪声段,检测的依据主要是语音和噪声的各种时频特性,其中,浊语音的周期性和谐波特性是一种广泛应用的特征。但是在行驶的汽车环境中,由于噪声非平稳且信噪比较低,这类特征较难得到可靠的检测。为此,本文根据浊音谐波结构的基本规律,利用时变噪声环境中各频带信噪比不同的特点,提出一种较为鲁棒的谐波快速检测算法。算法以较小的时频块为分析单元,利用一组基频在对数尺度上变化的谐波模板,自适应地搜索谐波结构清晰的部分,并以此检测浊语音信号。实验证明,该算法能够在行驶的汽车环境中达到较可靠的话音/非话音区别效果。     

水下连续波有源探测的回波检测算法

研究线性调频连续波在水下探测中的信号模型、回波信号的检测和目标参数估计方法,通过分析回波信号与发射信号间的差拍信号,提出差拍-分数阶傅里叶变换结构的处理算法。为了减少分数阶傅里叶变换二维搜索时的计算量,首先使用Radon-Ambiguity变换估计差拍信号的调频斜率,再做相应阶次的分数阶傅里叶变换。数值仿真说明提出的算法能够有效消除线性调频连续波的距离-速度耦合现象,准确估计目标参数。通过湖上试验比较线性调频脉冲信号和线性调频连续波的处理增益,提出的算法处理的连续波比匹配滤波方法处理的脉冲信号处理增益大13 dB。研究结果表明该算法在连续波水下探测中可行有效,不仅能够准确估计目标参数,还具有良好的检测性能。      

基于群速度失配的超声兰姆波二次谐波的时域测量方法

考虑到发射和接收换能器对超声兰姆波时域二次谐波信号所带来的不可避免的影响,提出一种基于基频与二倍频兰姆波群速度失配的超声兰姆波二次谐波的时域测量方法。当基频与二倍频超声兰姆波的相速度匹配而群速度失配时,在超声兰姆波传播过程中所发生的二次谐波信号,在时域上可与源于斜劈换能器的二次谐波信号相分离。采用仅源自于基频兰姆波的时域二次谐波的积分振幅,定量描述兰姆波二次谐波的发生效率。以铝板中传播的兰姆波为例,给出了时域二次谐波的具体测量过程。本文提出的测量方法放宽了超声兰姆波二次谐波的测量条件,且扣除了换能器对二次谐波信号所带来的影响,所测得的二次谐波信号完全来自于基频兰姆波时域信号的二次谐波发生效应。      

兴奋模式下谐波复合音音高感知机制的研究

通过测量谐波复合音的基频辨别阈,探讨中等"高次谐波"的音高感知是否依赖于谐波的可分离性,以及掩蔽音对实验结果的影响。实验方法:在目标音单独存在或目标音与掩蔽音混合时,将刺激通过高、中、低三个带通滤波器以获得不同的谐波可分离度。实验刺激设计为5种基频差异和4种相位组合。五名被试均为年轻人,纯音听阈≤15 dB HL。研究结果发现:谐波复合音的基频辨别阈随着信号频段的上移而增大;目标音和掩蔽音的基频差异对基频辨别阈有显著影响;但相位影响不显著。结论:谐波的可分离性对基频辨别阈有显著影响,但中等"高次谐波"的音高感知不依赖于可分离性;混合音的大部分音高感知结果与兴奋模式的峰值大小密切相关。      

一种声发射信号方位角自适应监测算法*

四阶累积量可用于声发射信号处理,结合盲波束形成算法可对声发射信号的方位角进行估计。由于四阶累积量的计算量较大,采用迭代计算的思想,提出一种基于四阶累积量的自适应声发射信号方位角监测算法。与改进前的算法相比,自适应算法的计算复杂度和所需存贮空间均显著降低,可用于声发射信号的方位估计和监测。计算机仿真及实测数据分析均验证了算法的有效性。     

基于扇区特征向量约束的稳健自适应匹配场处理器

自适应匹配场处理可以获得较高的定位精度和旁瓣抑制性能,但需要精确计算的拷贝场向量和参数搜索空间内的精细采样,这为自适应匹配场在实际复杂海洋环境中的实时应用造成了困难。本文提出了一种新的稳健自适应匹配场处理算法,用以同时克服环境参数失配和实时搜索计算量大这两个问题。新算法集成了邻点位置约束、环境扰动约束和扇区聚焦约束等三种自适应匹配场处理器的优点,采用扇区与环境扰动双重约束,不仅对环境参数失配更具宽容性,而且可确保目标位于扇区内的任何点时,主瓣增益损失较小。典型浅海环境下的数值仿真和实测数据分析表明,该算法在一定的环境失配条件下不仅能有效地检测定位目标,还能实现距离/深度平面内的大扇区目标搜索,可大大减小实时运算量。     

非线性负荷谐波传导的谐波系数算法与验证

谐波在电网侧的污染量不仅取决于非线性负荷发射, 更与谐波在整个系统中的传导息息相关,而目前关于谐波传导评估多采用直接的平均电流放大公式,并没有深入的研究不同谐波频次的综合影响,也鲜有明确的谐波系数算法。本文基于Parseval等式——Rayleigh能量定理,考虑谐波旁瓣频次,提出了一种针对非线性负荷谐波传导的谐波系数算法,弥补了根据单谱线平均电流放大倍数衡量谐波传导的不足。给出了基于非线性负荷的MATLAB仿真计算实例,并在EAST实验中通过与实测数据对比验证了其正确性。     

复杂噪声环境中的语音端点检测

提出了一种适用于复杂加性噪声环境的语音端点检测方法。通过对噪声类型的归纳,建立自适应的平稳噪声模型,并根据模型搜索信号能量非平稳的区域。然后基于浊音在频域上的谐波结构,在此区域内检测浊音,从而排除非平稳噪声的干扰。最后根据信号能量精确搜索语音起止点。与目前典型端点检测算法的对比实验表明,在大多数复杂噪声环境下,该算法具有较好的准确率。     

基于分数阶傅里叶变换的弹载SAR成像算法

针对弹载合成孔径雷达(SAR)回波信号的多普勒参数随斜距变化大及传统脉冲压缩成像算法分辨率低的问题,本文提出了一种基于分数阶傅里叶变换(FrFT)的弹载SAR成像算法.首先建立弹载SAR末制导阶段回波信号模型,然后通过局部最优处理来测量回波信号的调频率,并以此计算FrFT的最优阶次,在最优阶次下分别对回波信号进行距离向和方位向的FrFT,从而得到成像区域的SAR图像,最后分别采用传统脉冲压缩成像算法与本文基于FrFT的成像算法进行仿真和实测对比实验.实验结果表明,该算法能够对目标区域精确成像;由于在成像处理过程中,对每个距离向和方位向的回波信号进行独立的局部最优处理,因此该算法更适应于弹载SAR的非线性飞行轨迹,大大提高了弹载SAR的成像性能.该研究成果在目标探测与识别,精确制导等领域中具有重要的应用价值.     

无人机对地目标自动检测与跟踪技术

针对无人机图像帧序列具有平台高速运动,视角旋转强烈,需要实时处理等特点,提出一种基于双级旋转不变特征空间检测（粗匹配-精细匹配）与并行特征提取跟踪的无人机对地目标图像帧序列自动快速目标检测与跟踪算法。采用图像子块的平均灰度值、灰度值方差、灰度值梯度构建特征空间。通过构造图像特征空间的方法来快速筛选待匹配图像的可疑区域,删除大量的背景区域,检测算法使用全局初步匹配加局部精细匹配的方法来规避算法复杂度的缺陷。理论及实验分析表明:该算法实时性强,对图像的旋转畸变具有抵消作用,对异常情况可以恰当处理,且全局初步匹配流程具有可移植性,可以在其他图像匹配跟踪算法中充当预处理器。实验结果表明:该算法在无人机对地的情况下可以保证对地面目标的稳定跟踪,配套检测算法具有较好的实时性,满足无人机图像目标检测跟踪实时处理的需要。     

Error-compensating algorithms in phase-shifting interferometry: a comparison by error analysis

In this paper, two families of phase-shifting algorithms with π/2 phase steps are studied. In family I, three new algorithms are derived by using the averaging technique based on the Surrel six-sample algorithm with phase shifts of π/2. Family II includes four well-known algorithms derived by the averaging technique based on the conventional four-sample algorithm with π/2 phase steps. A polynomial model of phase-shift errors used to describe general expressions for calculation of the correct object phase via the Fourier spectra analysing method as a function of the harmonic order in the fringe signal is presented. The error-compensating properties of the algorithms in families I and II are investigated by the Fourier spectra analysing method. It is found that the averaging technique, when used in any of the algorithm with π/2 phase steps, can improve the phase-shifting algorithm property: it is insensitive to phase-shift error when the fringe signal contains the first harmonic, but it can't be used to enhance the phase-shifting algorithm properties when the fringe signal contains higher order harmonics (n2). P–V (peak–valley) phase errors are calculated by the computer simulation and tables and plots are presented, from which the algorithms in families I and II are compared. It is shown that the algorithms in family I are more insensitive to phase-shift errors when the fringe signal contains the second harmonic and the algorithms in family II are more insensitive to phase-shift errors when the fringe signal is a sinusoidal waveform.     

一种低速运动目标检测和识别的高阶累积量方法

强杂波背景下生命体运动低速目标的检测和识别是信号处理领域的难点.对采样数据的分析表明,生命体低速运动目标的回波信号可简化为正弦谐波过程,而墙体建筑物等固定物体杂波是高斯分布.因高斯分布杂波的高阶累积量为零,本文提出用高阶累积量方法抑制杂波,通过高阶谱分析和FFT积累,给出了目标检测和识别算法.实验结果表明,该方法构建的系统能穿透30 cm砖墙建筑物,探测出距离墙12 m远的人体低速运动目标信号.     

机载光电观瞄系统的瞄准线指向线性运动补偿方法

为方便操作员快速捕捉并瞄准目标,提出一种适用于机载光电观瞄系统的线性运动补偿方法。该方法借助地面目标相对载机在初始东北天坐标系下的速度矢量进行分解,得出目标相对光电系统在惯性坐标下的角速度,并根据解算出的角速度值实时进行伺服补偿,驱动光电转塔于手动模式下,当操作员不操控光电转塔时,系统的瞄准线能够自动地指向地面目标区域。该方法已在某型无人机用光电观瞄系统挂飞试验中进行了验证,结果表明:在电视观瞄具的小视场（0.70.5）下,地面目标点、瞄准线指向点相对载机点的张角在方位和俯仰方向均小于该视场的1/6。     

基于最优滤波器的强混沌背景中谐波信号检测方法研究

强混沌背景中的微弱谐波信号检测有重要的工程研究意义. 目前的检测方法主要是基于Takens理论的混沌相空间重构方法, 然而这些方法往往对信干噪比要求高, 且对高斯白噪声敏感等. 本文注意到混沌信号的二阶统计特性是不变的, 根据这个特点提出了一种基于最优滤波器的强混沌背景中的微弱谐波信号检测方法. 该方法首先构建一个数据矩阵, 在频域上对每个频率通道分别检测谐波信号, 从而将信号检测问题转化为最优化问题, 然后利用最优化理论设计滤波器, 使待检测频率通道的信号增益保持不变, 而尽量抑制其他频率通道的信号, 最后通过判断每一频率通道的输出信干噪比来检测谐波信号. 与传统方法相比, 本文方法有如下优点: 1)可以检测更低信干噪比下的微弱谐波信号; 2)可检测的信号幅度范围更大; 3)抗白噪声性能更强. 仿真结果证明了本文方法的有效性.     

Detection of an ultra-wideband quasi-radio signal with unknown arrival time against the background of white noise

We synthesize and analyze the maximum-likely detector of an ultra-wideband quasi-radio signal whose duration can be several periods or even a part of the period of harmonic oscillation with unknown amplitude, phase, and arrival time. Characteristics of the classical quadrature detector during reception of an ultra-wideband quasi-radio signal are found. The results of statistical simulation of detection algorithms are presented.     

基于FPGA的点目标滤波检测算法

介绍和分析了在当前成像跟踪系统中常用的几种点目标滤波检测算法。为了满足图像处理实时性要求，设计了一套针对图像滤波算法的FPGA硬件实现结构。该结构具有FPGA高速并行计算能力，能在信号读出的过程中实时地完成多种滤波处理。成像实验证明该方案切实可行，具有良好的实时滤波效果。     

Application of a Passive Polarimetric Infrared Sensor in Improved Detection and Classification of Targets

Automatic detection and recognition of targets by means of passive IR sensors suffer from limitations due to lack of sufficient contrast between the targets and their background, and among the facets of a target.In this paper the results of a suite of polarization-sensitive automatic target detection and recognition algorithms on sets of simulated and real polarimetric IR imagery are presented. A custom designed Polarimetric IR (PIR) imaging sensor is used for collecting real polarimetric target data-three of the four Stokes parameters under a variety of conditions. Then a set of novel algorithms are designed and tested that uses the target and background Stokes parameters for detection, segmentation and classification of targets.The empirical performance results are obtained in terms of the probabilities of detection, false alarm rate, segmentation accuracy, and recognition probabilities as functions of number of pixels on target, aspect and depression angles and under several background conditions (clutter densities) on the polarimetric and non-polarimetrirc data. These results show that a noticeable improvement over the non-polarimetric ATR can be achieved.     

Research on thermal wave processing of lock-in thermography based on analyzing image sequences for NDT

Lock-in thermography, an active IR thermography technique for NDT, is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. In this paper, thermal wave image sequences were sampled by a Cedip JADE MWIR 550 FPA infrared camera. Thermal wave signal processing algorithms are investigated to obtain information on subsurface defects. The Fourier transform, four-point correlation, and digital lock-in correlation algorithms are applied to extract the amplitude and phase of thermal wave’s harmonic component. A novel method called the time constant method (TCM) is proposed to analyze subsurface defects by using lock-in thermography. The experimental results confirm the thermal wave signal processing algorithms’ efficiency on subsurface defect detection.     

Scale-space point spread function based framework to boost infrared target detection algorithms

Small target detection is one of the major concern in the development of infrared surveillance systems. Detection algorithms based on Gaussian target modeling have attracted most attention from researchers in this field. However, the lack of accurate target modeling limits the performance of this type of infrared small target detection algorithms. In this paper, signal to clutter ratio (SCR) improvement mechanism based on the matched filter is described in detail and effect of Point Spread Function (PSF) on the intensity and spatial distribution of the target pixels is clarified comprehensively. In the following, a new parametric model for small infrared targets is developed based on the PSF of imaging system which can be considered as a matched filter. Based on this model, a new framework to boost model-based infrared target detection algorithms is presented. In order to show the performance of this new framework, the proposed model is adopted in Laplacian scale-space algorithms which is a well-known algorithm in the small infrared target detection field. Simulation results show that the proposed framework has better detection performance in comparison with the Gaussian one and improves the overall performance of IRST system. By analyzing the performance of the proposed algorithm based on this new framework in a quantitative manner, this new framework shows at least 20% improvement in the output SCR values in comparison with Laplacian of Gaussian (LoG) algorithm.