Probabilistic characteristics of signal detection by a spatial correlation filter

Results of theoretical and model studies of the probabilistic characteristics of signal detection by a spatial correlation filter are described. A mathematical model of signal processing in the spatial correlation filter is presented. Expressions for estimating the detection probability, missed detection probability, false alarm probability, and threshold level, as well as expressions for choosing the optimal filter parameters to obtain preset probability characteristics, are derived on the basis of this model. Results of computer simulation of the probabilistic characteristics of signal detection by spatial correlation filters with random arrays are shown to corroborate the theoretical findings obtained within the model.     

扫描型红外预警系统中弱小目标的检测算法

提出一种基于面阵探测器的全方位红外预警系统的运动弱小目标检测算法.该算法主要基于灰度形态学滤波和目标概率分布函数匹配两种技术.灰度形态学的高帽变换可以有效地检测出红外图像中的特定目标,但没有考虑目标强度分布特征,检测结果的虚警率较高.本文采用了均值偏移算法常用的概率分布函数匹配技术,对检测出的小目标进行二次确认.试验结果表明,该方法能够有效地抑制背景杂波干扰,降低虚警率.     

时空域双边滤波背景抑制算法研究

红外图像中的强边缘一直是制约红外弱小目标检测概率的重要因素,同时是产生目标虚警的重要来源。采用能够同时利用邻域空间欧式距离和灰度值相似性的双边滤波,并针对天基红外系统中帧间背景缓慢变化的特点,设计一种基于时空域的双边滤波法,实验验证该方法对复杂背景的强边缘具有很好地抑制效果,信杂比增益大于3.6,同时能够很好地保留目标能量,目标能量损失因子D factor小于0.2,有效地提高目标的局域信杂比。     

An adaptive clutter rejection method based on AR model in color flow imaging

The ultrasound Doppler signal scattered from blood is heavily corrupted by the clutter signal reflected from slowly moving muscular tissue. The Doppler frequency shift of blood flow and clutter in different parts of human body greatly changes. Therefore, if a fixed wall filter is selected, the optimal filtering effect can not be attained. An adaptive clutter rejection method is proposed in this paper, which consists of a weak clutter rejector and a 2-order AR estimator. The clutter and blood power thresholds were preliminary defined in the weak clutter rejector. The echo power is compared with the two pre-defined thresholds, and the result was used to select an appropriate wall filter. The output of the weak clutter rejector is estimated by a 2-order AR estimator and two poles are acquired. The low frequency pole denotes the clutter signal and the high frequency pole denotes the blood signal. Before the AR estimation, a static signal is added to avoid producing split spectral peaks. It is illustrated in the simulation that the proposed method can detect the slower blood flow with smaller variance compared with the traditional wall filtering method.     

多光谱目标探测的波段选择

利用超光谱数据对多光谱传感器的波段选择提出了一个框架。根据探测理论,导出了一个代价函数,对于区分弱小目标和杂波(光谱分布已知)的探测性能最优的光谱波段来说,可使该函数最小。利用匹配追踪算法找到了一个近似最小的代价函数,从而选出了滤波器。该方法可用于设计多光谱红外搜索跟踪和光电导弹预警传感器。在杂波背景下,对小目标探测的低虚警率和高探测概率来说是至关重要的。     

多量级多向梯度海空复杂背景红外弱点目标检测

由于红外图像一般带有较大的噪声，采用传统的目标检测方法效果不理想。本文提出了一种新的海空背景下受强杂波和噪声污染的红外图像弱点目标检测算法。用多个量级梯度对图像目标进行检测，并对检测的结果进行了表决融合。结果表明，基于表决融合的多量级多向梯度检测消除了云层、海浪和海天线等背景干扰，在实现高检测概率的同时，不仅可以达到较低的虚警概率，而且可检测信杂比为1的点目标。     

导模共振效应光子晶体滤波器光谱检测稳定性的研究

由于光子晶体滤波器带宽窄和高灵敏度的特点,检测抗体含量极限可以达到ng·mL-1。可以应用于生物传感器监测生物大分子内部反应过程。一维光子晶体滤波器作为生物传感器换能元件将生物信息转化为可检测的光电信号信息,主要反应在光谱仪测得共振波峰所在波长的变化。精确测试时,检测传感系统的稳定性是首要考虑的关键因素。稳定性决定实验数据的有效性。该工作对所制备的基于导模共振效应的一维光子晶体滤波器结构进行形貌和光谱测试,介绍了实验室所搭建的实时检测传感系统。由于系统集成度、 耦合损耗等因素的影响,光谱信息出现一定的噪声信号。因此,重点提出利用Lab VIEW编程实时监控光子晶体滤波器共振波峰值随时间的变化,由光谱变化情况来反应本套检测系统的稳定性和测试数据的有效性。同时这种实时监控程序也可用来监控其他基于导模共振生物传感系统的稳定度。该检测系统由于震动,光源抖动等问题产生的共振峰值漂移为0.25 nm,通过与模拟计算结果比较可以判定系统稳定性可以达到试剂检测的要求。     

强杂波背景红外弱小目标检测算法

针对强杂波背景远距离红外弱小信号目标的特点,提出了一种基于自适应滤波的红外弱小信号检测方法。算法首先对图像进行消噪声处理,其次运用自适应滤波方式消除背景增强目标信号,最后进行基于点源目标(试验采集)成像信号特性的判决法则删除虚假目标,算法有效解决了光电探测设备高检测概率与低虚警率的矛盾。实验结果表明:该方法能够在单帧图像上有效提取出小区域信噪比为4的弱小信号目标,检测概率不低于0.75,虚警率不高于1次/100帧。     

强杂波背景红外弱小目标检测算法

针对强杂波背景远距离红外弱小信号目标的特点,提出了一种基于自适应滤波的红外弱小信号检测方法。算法首先对图像进行消噪声处理,其次运用自适应滤波方式消除背景增强目标信号,最后进行基于点源目标（试验采集）成像信号特性的判决法则删除虚假目标,算法有效解决了光电探测设备高检测概率与低虚警率的矛盾。实验结果表明：该方法能够在单帧图像上有效提取出小区域信噪比为4的弱小信号目标,检测概率不低于0.75,虚警率不高于1次/100帧。     

Complex background suppression based on fusion of morphological Open filter and nucleus similar pixels bilateral filter

To reduce the influences of the heavy clutter on infrared small target detection, a new background suppression algorithm is presented in this paper which depends on fusion of two different filters. The Nucleus Similarity Degree (NSD) of each pixel is analyzed first, then morphological Open filter which favors point target enhancement and the Nucleus Similar Pixels Bilateral Filter (NSPBF) which favors background prediction are fused. The complex background suppression and target enhancement can be accomplished more effectively by the fusion. Experimental results indicates that the method is efficient for background suppression under the condition of heavy clutter.     

Principal component analysis for emergent acoustic signal detection with supporting simulation results

A method is introduced that uses principal component analysis (PCA) to detect emergent acoustic signals. Emergent signal detection is frequently used in radar applications to detect signals of interest in background clutter and in cognitive radio to detect the primary user in a frequency band. The method presented differs from other standard techniques in that the detection of the signal of interest is accomplished by detecting a change in the covariance between two channels of data instead of detecting the change in statistics of a single channel of data. For this paper, PCA is able to detect emergent acoustic signals by detecting when there is a change in the eigenvalue subspace of the covariance matrix caused by the addition of the signal of interest. The algorithm's performance is compared to an energy detector and the Neyman-Pearson theorem. Acoustic simulations were used to verify the performance of the algorithm. Simulations were also used to examine the effectiveness of the algorithm under various signal-to-interferer and signal-to-noise ratios, and using various test signals.     

时变信道相干部分的修正匹配

由于水声信道的随机时变及多途特性,使得以发射信号作参考的匹配滤波器检测性能的下降。本文提出当多途结构具有相对稳定部分时,可采用以下两种信道匹配方法:（1）脉间相关信道匹配法（参见[4]）;（2）解卷求信道响应法,后一方法要求发射宽带短脉冲,用解卷求出的信道响应h（τ,ι）去修正欲发射的其它声呐信号,并把它当作匹配滤波器的响应函数,以提高匹配滤波器对时变信道的适配能力。本文前一部分对各种设定的信道模型,给出了修正匹配的计算机模拟结果;后一部分给出了经4浬和24浬海洋信道传输的数据的修正匹配,并给出了以上两部分修正前后的计算机结果比较。对大信噪比,修正匹配的效果是十分显著的。     

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

In marine radar target detection, sea clutter will cause a large number of missed alarms and false alarms, which will affect the accuracy of target detection. In order to suppress sea clutter effectively, a sea clutter suppression and target detection algorithm of marine radar image sequence based on spatio-temporal domain joint filtering is proposed in this paper. The proposed method is to add a sea clutter suppression link before detecting the target. Firstly, the marine radar image sequence is transformed into three-dimensional frequency wavenumber domain by three-dimensional fast Fourier transform (3D-FFT), and then the three-dimensional image spectrum is obtained. According to the fact that the sea clutter spectrum obtained from the image spectrum satisfies the dispersion relation of linear wave theory in the three-dimensional frequency wavenumber domain, a sea clutter model is established. Then, through the established sea clutter model, a spatio-temporal domain joint sea clutter suppressor is designed to filter the image spectrum. After that, the filtered image spectrum is transformed by three-dimensional inverse fast Fourier transform (3D-IFFT) to obtain the image sequence in which sea clutter is suppressed. Finally, target detection is carried out for sea clutter suppressed image sequence. The method is validated by using the real data of X-band marine radar. Compared with the classical Empirical mode decomposition (EMD) method, the improvement of signal-to-noise ratio (SNR) is more obvious, and SNR can be increased by 15.3 db at most. In addition, compared with target detection on original images directly, the proposed method has excellent detection rate and can increase detection rates by at least 8%.     

一种背景自适应调整的弱点目标探测算法

针对因复杂背景导致低信噪比的弱点目标探测率降低的问题,首先分析了从红外图像中探测弱点目标时,由于复杂和缓变背景下潜在目标探测率不同,而导致目标探测率降低的理论依据;并在该分析的基础上,提出了一种基于背景自适应调整的红外点目标探测算法。该方法利用鲁宾逊(Robinson)保护滤波器从经过预处理的图像中提取潜在目标;通过复杂背景模糊隶属度函数将图像映射到模糊特征平面,并由该特征平面计算背景调整因子,以对提取的潜在目标进行加权调整,从而降低了复杂背景的影响。实验结果表明,该算法可以显著提高复杂背景下红外点目标的检测概率,并且能够探测出信噪比为1的目标。     

Differentiation and subtraction of amplitude and phase images using a photorefractive novelty filter

In this article, we demonstrate the capability of a two-beam coupling photorefractive optical novelty filter of detecting changes in the amplitude or phase of optical images. These changes may either be continuous or discrete in time. The performance of the two-beam coupling novelty filter is investigated and expressions for the output contrast corresponding to phase and amplitude changes based on a novel, simple interference model of two-beam coupling are derived. These expressions are verified by experimental results on the novelty contrast, revealing that the amplitude contrast is not described correctly by the commonly accepted coupled-wave theory. The novelty filter was applied to the detection of temporally continuous phase changes provided by a gas flow and moving microscopic objects. A novel scheme for image subtraction is also demonstrated, showing the novelty filter’s ability to detect temporally discrete changes. Received: 14 November 1998 / Revised version: 18 January 1999 / Published online: 12 April 1999     

基于复滤波器组的红外弱小目标检测算法

为了有效抑制复杂背景的干扰,降低复杂背景所带来的虚警,提高目标检测的信噪比,提出了一种基于复滤波器组的红外弱小目标检测算法。分析了复杂背景下带有弱小目标的红外图像中复杂背景和弱小目标图像各自的频谱特性,并引入了分频段处理的思想。比较了各种滤波器的性能,并选用了基于复小波的滤波器组,用该滤波器组将红外弱小目标图像分解到各个子频域;对分解后的各频段图像分别进行基于罗宾逊滤波的目标检测处理,提取各频段图像中的奇异点;根据目标图像和背景图像的频谱特性的定量分析结果,选取合适的权值,将各频段检测的结果进行加权融合,得到最终的处理效果。实验结果表明:弱小目标检测方法较之于传统的不分频段的高通滤波处理方式可以获得更高的信噪比,目标得到明显的增强,背景杂波得到更有效的抑制,各项探测指标均更优。     

基于运动补偿的红外图像噪音时域IIR滤波算法

从模式识别的角度出发将图像分为运动区域和非运动区域,采用基于噪音分布模型的运动检测技术与基于概率松弛法的运动区域标号技术相结合对这两种区域进行具体划分,对分类后的图像采用时域IIR滤波,不同区域采用不同的影响因子,以期达到最终的运动补偿.仿真结果表明该方法有效抑制了噪音,同时并未引起明显的运动模糊,图像的视觉效果得到了极大改善.     

人全血的毛细管显微拉曼光谱分析

血液中含有众多生物信息,如激素、酶、抗体等丰富的蛋白质成分。通过对血液中众多生物信息进行检测鉴定可以起到对该血液种属判定、溯源的目的。因此,血液检测技术的发展在诸如刑事案件侦破、物种鉴定、疾症预防等领域具有重要意义。目前,传统血液检测手段多为显微观测、免疫法、DNA/基因检测法等,这些技术会对血液样本造成不可逆转的破坏性,且存在分析周期长、结构装置复杂、试验价格昂贵等问题。随着激光技术的发展,拉曼光谱技术作为一种非线性散射光谱技术,在血液检测技术中得到了应用。在血液检测技术中,拉曼光谱技术通常与共聚焦显微系统结合,对涂在载玻片上或盛放在透明容器中的血液样品进行光谱信号采集。该技术具有快速、无损等优势,但复杂的光路系统及昂贵的实验装置限制了该技术的广泛推广。为提出一种装置简单、操作简便的血液拉曼检测新技术,研究采用基于毛细管的显微拉曼技术方案采集并分析人全血的拉曼信号。血液样品通过毛细管的虹吸效应取样,与载玻片的涂样方式相比毛细管的方案具有模拟人血管、维持血液活性、减小空气对实验过程中血液成分的影响、降低激光对血液样品的灼伤效果等优势。为避开可见光部分荧光较强区域的荧光干扰,研究采用360 nm紫外激光器作为激发光源,防止可见荧光信号的干扰。积分时间设为800 ms,有效避免因激光长时间照射对血液样品的灼伤效果,影响实验数据的稳定性与真实性,光谱平均次数为2次,避免单次测量所带来的数据的不准确性影响。光谱扫描范围为500～1 800 cm-1, 结果表明此范围内可较好的避开可见光部分荧光较强区域的干扰。测得的拉曼光谱信号通过滤波去噪及基线校正进行处理。首先采用5阶离散小波变换滤波,进行1层信号分解,滤除高频噪声信号,保留低频有效信号,从而去除杂散信号,对光谱有效信号进行提取。其次,采用4阶多项式拟合扣除基底的基线校正,实现人全血的毛细管显微拉曼光谱峰值信号的提取。最终,通过查询SDBS数据库以及人血样本通过reishaw共聚焦显微拉曼光谱仪测量所得光谱图进行验证发现测得信号中部分为人体内数种氨基酸成分的拉曼信号。实验研究发现,基于毛细管的显微拉曼实验系统与常规拉曼探头实验系统相比,拉曼信号更稳定、重复性高,可有效提取人全血中的拉曼光谱信号, 而其与高精度的共聚焦显微拉曼系统相比价格便宜、结构简单、易于推广等优点,但信号信噪比、有效信号的峰值强度上仍有进一步的提升,是一种测量人全血拉曼信号的可行方案。     

Time and direction of arrival detection and filtering for imaging in strongly scattering random media

We study detection and imaging of small reflectors in heavy clutter, using an array of transducers that emits and receives sound waves. Heavy clutter means that multiple scattering of the waves in the heterogeneous host medium is strong and overwhelms the arrivals from the small reflectors. Building on the adaptive time-frequency filter of [Borcea et al, SIIMS 2011;4(3)], we propose a robust method for detecting the direction of arrival of the direct echoes from the small reflectors, and suppressing the unwanted clutter backscatter. This improves the resolution of imaging. We illustrate the performance of the method with realistic numerical simulations in a non-destructive testing setup.     

Design of correlation filters for pattern recognition using a noisy reference

We present the design of correlation filters for detection of a target in a noisy input scene when the object of interest is given in a noisy reference image. The target signal, shape and location in the reference image are assumed to be unknown. Two signal models are considered for the input scene: additive and nonoverlapping. The design of the filters consists of automated estimation of needed parameters from a noisy reference image and maximization of the peak-to-output energy ratio criterion. Two filter variants are proposed. The matching error metric is used to determine the regions of the parameter space where each filter variant performs better. Computer simulation results obtained with the proposed filters are presented and evaluated in terms of discrimination capability, location errors, and tolerance to input noise.