Bilateral two-dimensional least mean square filter for infrared small target detection

The basic TDLMS (Two-Dimensional Least Mean Square) filter fails to detect infrared small targets consistently, especially under conditions of heavy noise and distinct cloud edges. This paper proposes a robust and efficient small-target detection method based on the basic TDLMS filter. The method first smooths the input image with a Gaussian filter of adaptive variance, and then employs TDLMS with a selected step size to filter the image with rightward and leftward iterations. Two prediction error images are obtained by subtracting the prediction images of the bilateral filtering from the original input image. Each prediction error image is separated into positive and negative prediction error images. That is, four images are generated in the bilateral filtering. The final image is obtained by fusing these four images. Experimental results show that the proposed method achieves significant improvement in background suppression and detection performance over the basic TDLMS filter and other improved TDLMS filters.     

Multiband processing of multimode light: combining 3D photonic lanterns with waveguide Bragg gratings

The first demonstration of narrowband spectral filtering of multimode light on a 3D integrated photonic chip using photonic lanterns and waveguide Bragg gratings is reported. The photonic lanterns with multi‐notch waveguide Bragg gratings were fabricated using the femtosecond direct‐write technique in boro‐aluminosilicate glass (Corning, Eagle 2000). Transmission dips of up to 5 dB were measured in both photonic lanterns and reference single‐mode waveguides with 10.4‐mm‐long gratings. The result demonstrates efficient and symmetrical performance of each of the gratings in the photonic lantern. Such devices will be beneficial to space‐division multiplexed communication systems as well as for units for astronomical instrumentation for suppression of the atmospheric telluric emission from OH lines.     

A practical radio frequency fingerprinting scheme for mobile phones identification

Radio frequency fingerprint (RFF) has attracted a remarkable surge of attention to wireless transmitter identification due to the inimitable hardware imperfection. However, most RFF-based schemes devised in controlled environments are unable to reach the claimed performance in real-world scenarios. This paper proposes a practical RFF identification method for mobile phones in Global System for Mobile (GSM) system. Specifically, the instantaneous amplitude of near-transient part in normal burst (NB) is regarded as RFF that extracted from up-link communications. In addition, an anomaly filtering and stacking (AFS) method is introduced to obtain stable RFF in Time Division Multiple Access (TDMA) system. Lastly, the impacts of frequency point and sending power variations on RFF are fully dissected in comparison experiments. Experiments on 10 mobile phones show that the proposed RFF scheme yields 99.17% True Acceptance Rate (TAR) in real wireless environments. Experiments also show that the varying transmission power decreases the accuracy of RFF identification.     

Iterative filtered ghost imaging

It is generally believed that, in ghost imaging, there has to be a compromise between resolution and visibility. Here we propose and demonstrate an iterative filtered ghost imaging scheme whereby a super-resolution image of a grayscale object is achieved, while at the same time the signal-to-noise ratio (SNR) and visibility are greatly improved, without adding complexity. The dependence of the SNR, visibility, and resolution on the number of iterations is also investigated and discussed. Moreover, with the use of compressed sensing the sampling number can be reduced to less than 1% of the Nyquist limit, while maintaining image quality with a resolution that can exceed the Rayleigh diffraction bound by more than a factor of 10.     

Quantised phase filters with binary low and high pass amplitude response: the effect of quantisation for scale and rotation input distortions

In the field of optical pattern recognition, there are a large number of filters that possess identification capabilities for certain kinds of input distortions. The resolution of the spectral components plays an important role in the overall processing time of a correlator that may employ such filters. In this paper, two different techniques are discussed: low pass phase filtering and high pass phase filtering. This is achieved by binarizing the amplitude information which then allows certain frequencies to pass and others to be blocked. Their response to different kinds of input distortions is presented and the effect of phase quantisation is considered in detail.     

Wavelet and harmonic filtering for distortion-invariant volume holographic correlation

The wavelet and harmonic filtering method suggested by Zalevsky and Ouzieli is introduced in this paper and adopted in our volume holographic image recognition system. This composite filter combines several scaled versions of the cascaded wavelet and harmonic filter, obtaining high discrimination ability and wide dynamic range of rotation and scale deformations. Optical experiments are conducted to demonstrate the validity and practicability of the algorithm. To the best of our knowledge, this is the first report of using this algorithm in a volume holographic system. Moreover, the separate correlation approach proposed in this paper greatly simplifies the manufacturing process and reduces the cost of the system.     

A Maximum Entropy Method for Particle Filtering

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.     

Unscented fuzzy-controlled current statistic model and adaptive filtering for tracking maneuvering targets

A novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. A fuzzy system allows the filter to tune the magnitude of maximum accelerations to adapt to different target maneuvers, and unscented transformation can effectively handle nonlinear system. A bearing-only tracking scenario simulation results show the proposed algorithm has a robust advantage over a wide range of maneuvers and overcomes the shortcoming of the traditional current statistic model and adaptive filtering algorithm.     

Absorption spectra and the nature of complexes in the polyvinyl Alcohol-Nickel (II) chloride system

We have used electronic spectroscopy in the 160–1100 nm range to study the polyvinyl alcohol-nickel(II) chloride system. Based on the results obtained, we hypothesize formation of mixed-ligand complexes of the type [Ni(H₂O)_6-nCl_n]^2-n (n = 0, 1,..., 5) in the polyvinyl alcohol matrix. Transformation of the coordination sphere as the NiCl₂ concentration changes is apparent both in the region of the d-d transition bands (350–1100 nm) and in the region of the charge transfer bands (160–250 nm). We propose assigning the absorption bands separated by mathematical treatment to complexes of specific compositions. __________ Translated from Zhurnal Prikladnoi Spektroskopii, Vol. 73, No. 1, pp. 136–138, January–February, 2006.     

因特网防御DoS攻击技术评述Ⅰ--攻击分类与特征·包过滤·攻击检测与防御

概述了因特网上DoS攻击的相应分类及基本特征，评述了包过滤、攻击检测及防御技术的最新成果．前一部分介绍了入口过滤、基于路由的过滤网和有效源地址强制协议．后一方面主要讨论了适合于检测攻击包的技术，介绍了新近提出的频谱分析方法和泛滥检测系统．简要评述了已有的防御SYN泛滥攻击的技术措施，介绍了Cisco的TCP拦截技术，提出了改进策略．