基于强耦合Duffing振子的微弱脉冲信号检测与参数估计

耦合Duffing振子在检测强噪声中的微弱脉冲信号时具有可检测信噪比低等优点,但目前检测模型还存在系统性能与初始状态有关、只能工作在倍周期分岔状态等缺陷.为此本文构建了一种能克服上述缺点的新的微弱脉冲信号检测模型,通过对两个Duffing振子同时施加较大的恢复力和阻尼力耦合,可使振子间产生广义的"阱内失同步"现象,基于这种现象可实现微弱脉冲信号的检测与恢复.以信噪比改善和波形相似度为衡量指标,研究了周期策动力幅值与周期、耦合系数、计算步长、阻尼系数等参量对模型信号检测与波形恢复效果的影响.对方波、双指数脉冲和高斯导数脉冲进行检测和恢复的实验结果表明,本文所构建的模型能够在较低信噪比条件下有效地检测并恢复出高斯白噪声背景中的微弱脉冲信号,进而改善了现有的Duffing振子对非周期脉冲信号的检测能力并扩展了其应用领域.     

On the Higgs feature of gravity

The gauge gravitation theory, based on the equivalence principle besides the gauge principle, is formulated in the fibre bundle terms. The correlation between gauge geometry on spinor bundles describing Dirac fermion fields and space-time geometry on a tangent bundle is investigated. We show that field functions of fermion fields in presence of different gravitational fields are always written with respect to different reference frames. Therefore, the conventional quantization procedure is applicable to fermion fields only if gravitational field is fixed. Quantum gravitational fields violate the above mentioned correlation between two geometries.     

Duffing振子微弱信号检测盲区消除及检测统计量构造

针对Duffing振子进行同频微弱信号检测时存在的检测盲区, 提出了一种策动力移相法予以消除. 结合微弱信号特性对检测盲区表达式进行分析, 得出了策动力与待测信号的“相差”位于检测盲区时的角度范围, 通过使策动力相位产生相移量π后实现对同频信号的检测, 实验证明了方法的可行性. 为了克服定性分析的不足和有效区分振子系统信号检测过程中出现的不同状态, 构造了一个基于类Halmiton系统的检测统计量, 并设计了基于该统计量的任意频率信号检测方法步骤, 方法的核心是以检测统计量出现极大值处所在的连续两个频点作为待测信号的频率范围. 在不同检测过程的仿真实验基础上, 给出了混沌、间歇混沌和大周期的检测统计量数值范围, 进而利用该数值范围作为判据实现了对任意频率信号的检测. 实验结果表明, 该方法不仅为系统状态提供了定量的判据准则, 而且提高了信号检测性能, 进一步完善了现有利用Duffing振子进行微弱信号检测的方法.     

虚拟时间反转水声信号检测

针对目标辐射声信号特性未知的情况,在不增加额外水声换能器的条件下,研究提高水听器阵列对水声信号检测性能的方法。首先,按照经典二元检测问题处理方法分析了常规能量检测方法的性能,在此基础上,根据虚拟时间反转处理原理,对处理后的信号构建检测统计量,推导得到了虚拟时间反转检测方法的理论门限和检测性能的表达式,并通过与常规能量检测的对比分析了虚拟时间反转检测的处理增益。使用计算机仿真实验从声源频率、接收阵列阵元数、目标距离与深度等方面分析了两种方法的检测性能。结果表明,所提出的算法相对于常规能量检测算法在性能上有显著优势,且接收阵元数是对算法性能影响最为明显的因素。      

New multivariate noise model and data detection using the expectation maximization algorithm

A signal sequence detector in a high areal density recording channel is required to provide robust compensation against unexpected error events. Primarily, a number of error events are caused by media noise and nonlinear distortion. The same problem of signal sequence detection remains to be solved in a future magnetic recording system that comes in predisposed to trend for recording by large-sector size instead of existing single-sector one that consists of 512 information 8-bits bytes. For the above problem, this paper shows the signal estimation method based on statistical inference for such a finite mixture model with known number of degraded noise components. Our signal detection scheme with multivariate autoregressive models for total noise and the expectation maximization algorithm is applied to maximum a posteriori estimation for multivariate mixtures of noise. Furthermore, a non-binary low-density parity-check (LDPC) code is used for an error-correcting code that satisfies the specific run-length limited condition in the proposed system. It shows that the proposed error-correcting and signal detection methods are effective in estimating signal sequences degraded by media noise and in improving the error rate performances with respect to the conventional system using the binary LDPC code and univariate autoregressive model.     

一种基于广义Duffing振子的水中弱目标检测方法

海洋环境中,在水下目标的线谱频率未知或者目标辐射噪声的连续谱很弱时,很难实现水中弱目标的准确检测,本文提出基于广义Duffing振子检测系统的水下目标辐射噪声检测方法.通过对传统周期扰动的Duffing振子信号检测系统的分析和推广,提出了一种可输入非周期、非平稳信号的广义Duffing振子检测系统,可检测输入的无先验信息目标信号.为实现广义Duffing振子系统运动状态的精确、有效判断,提出了一种相空间图形的离散分布列计算方法,通过类网格函数实现了利用统计复杂度对系统输出的嵌入式表征,从而实现了无先验信息时的水中弱目标的嵌入式检测.相同条件下与传统检测方法仿真对比可知,本文提出的方法可以检测到更低信噪比下的目标,并能满足水中检测实时性要求.     

Digital detection and processing of multiple quadrature harmonics for EPR spectroscopy

A quadrature digital receiver and associated signal estimation procedure are reported for L-band electron paramagnetic resonance (EPR) spectroscopy. The approach provides simultaneous acquisition and joint processing of multiple harmonics in both in-phase and out-of-phase channels. The digital receiver, based on a high-speed dual-channel analog-to-digital converter, allows direct digital down-conversion with heterodyne processing using digital capture of the microwave reference signal. Thus, the receiver avoids noise and nonlinearity associated with analog mixers. Also, the architecture allows for low-Q anti-alias filtering and does not require the sampling frequency to be time-locked to the microwave reference. A noise model applicable for arbitrary contributions of oscillator phase noise is presented, and a corresponding maximum-likelihood estimator of unknown parameters is also reported. The signal processing is applicable for Lorentzian lineshape under nonsaturating conditions. The estimation is carried out using a convergent iterative algorithm capable of jointly processing the in-phase and out-of-phase data in the presence of phase noise and unknown microwave phase. Cramér-Rao bound analysis and simulation results demonstrate a significant reduction in linewidth estimation error using quadrature detection, for both low and high values of phase noise. EPR spectroscopic data are also reported for illustration.     

High resolution time-delay estimation of underwater target geometric scattering

The geometric scatterings carry the information of the shape of an underwater target. While the time-delay of the weak geometric scattering exists in the received signal cannot be obtained accurately by the conventional time-delay estimation methods because of the limit of the main-lobe width and the interferences from the side-lobe. In this paper, we propose a high resolution time-delay estimation (HRTDE) scheme consisting of two steps. Firstly, when a linear-frequency-modulated (LFM) pulse is transmitted by sonar, the dechirping method transforms the geometric scatterings with different time-delays into multiple single-frequency components respectively, in which the frequency of the dechirped signal shows a linear relationship with the time-delay of the geometric scattering. Then the multiple signal classification (MUSIC) algorithm is adopted to increase the spectrum resolution when multiple single-frequency signals exist in the dechirped signal and the frequency interval is smaller than the frequency resolution limit of the Fourier transform. Simulation results show that the main lobe of the proposed scheme is sharper and with less interference from the side-lobe, compared with the conventional time-delay estimation methods. The results from the anechoic pool experiment demonstrate that the proposed scheme achieves a better time-delay estimation performance for the weak geometric scattering generated by the bottom edge of the underwater target model than match filter based methods.     

Fault Detection Based on Multi-Dimensional KDE and Jensen–Shannon Divergence

Weak fault signals, high coupling data, and unknown faults commonly exist in fault diagnosis systems, causing low detection and identification performance of fault diagnosis methods based on T2 statistics or cross entropy. This paper proposes a new fault diagnosis method based on optimal bandwidth kernel density estimation (KDE) and Jensen–Shannon (JS) divergence distribution for improved fault detection performance. KDE addresses weak signal and coupling fault detection, and JS divergence addresses unknown fault detection. Firstly, the formula and algorithm of the optimal bandwidth of multidimensional KDE are presented, and the convergence of the algorithm is proved. Secondly, the difference in JS divergence between the data is obtained based on the optimal KDE and used for fault detection. Finally, the fault diagnosis experiment based on the bearing data from Case Western Reserve University Bearing Data Center is conducted. The results show that for known faults, the proposed method has 10% and 2% higher detection rate than T2 statistics and the cross entropy method, respectively. For unknown faults, T2 statistics cannot effectively detect faults, and the proposed method has approximately 15% higher detection rate than the cross entropy method. Thus, the proposed method can effectively improve the fault detection rate.     

Direct experimental characterization of the Bose-Einstein distribution of spatial fluctuations of spontaneous parametric down-conversion

We present, to the best of our knowledge, the first experimental demonstration by direct detection of the Bose-Einstein photon-number distribution of highly spatially multi-mode but temporally single mode spontaneous parametric down-conversion.Received: 20 November 2003, Published online: 6 January 2004PACS: 42.50.-p Quantum optics - 42.50.Ar Photon statistics and coherence theory - 42.65.-k Nonlinear optics - 42.65.Lm Parametric down conversion and production of entangled photons     

基于复小波包分形理论的爬壁机器人故障检测

通过研究爬壁式机器人的控制和运动特征，提出一种基于复小波包分形理论的故障检测方法．利用复小波包的平移不变性，将爬壁式机器人传感器输出信号分解成独立的频谱，并进行阀值处理和重构，从而有效去除高频噪音并提取故障的特征频率；依据信号分形维数的多尺度不变性，在嵌入维数空间，采用维数最大距离法，确定复小波包域故障信号的关联雏数．仿真实验表明，爬壁式机器人在各种异常工作模式下的故障信号关联维数能比较真实地反映其故障状态空间，同时也验证了故障信号的关联维数低于正常信号的关联维数作为故障发生与否的定量判据的正确性．     

Error Estimation at the Information Reconciliation Stage of Quantum Key Distribution

Quantum key distribution (QKD) offers a practical solution for secure communication between two distinct parties via a quantum channel and an authentic public channel. In this work, we consider different approaches to the quantum bit error rate (QBER) estimation at the information reconciliation stage of the post-processing procedure. For reconciliation schemes employing low-density parity-check (LDPC) codes, we develop a novel syndrome-based QBER estimation algorithm. The algorithm suggested is suitable for irregular LDPC codes and takes into account punctured and shortened bits. Testing our approach in a real QKD setup, we show that an approach combining the proposed algorithm with conventional QBER estimation techniques allows one to improve the accuracy of the QBER estimation.     

An intelligent background‐correction algorithm for highly fluorescent samples in Raman spectroscopy

Fluorescent background is a major problem in recoding the Raman spectra of many samples, which swamps or obscures the Raman signals. The background should be suppressed in order to perform further qualitative or quantitative analysis of the spectra. For this purpose, an intelligent background‐correction algorithm is developed, which simulates manual background‐correction procedure intelligently. It basically consists of three aspects: (1) accurate peak position detection in the Raman spectrum by continuous wavelet transform (CWT) with the Mexican Hat wavelet as the mother wavelet; (2) peak‐width estimation by signal‐to‐noise ratio (SNR) enhancing derivative calculation based on CWT but with the Haar wavelet as the mother wavelet; and (3) background fitting using penalized least squares with binary masks. This algorithm does not require any preprocessing step for transforming the spectrum into the wavelet space and can suppress the fluorescent background of Raman spectra intelligently and validly. The algorithm is implemented in R language and available as open source software ( http://code.google.com/p/baselinewavelet ). Copyright © 2009 John Wiley & Sons, Ltd.     

应用于视频编码的实时多测度联合突变场景切换检测算法

提出一种与视频编码器共用运动搜索模块的实时场景切换检测算法.通过分析原始图像与其运动补偿图像的一阶与二阶差值信号统计特性,分别构造对应于不同场景切换类型的两种测度函数,并联合使用该测度函数检测突变场景切换,同时自适应调节每个测度函数输出值的判决门限.分析和实验结果表明,该算法在视频编码位移估值基础上只增加少量的计算,而对视频序列中的突变场景切换检测的查全率和查准率均优于已有的几种实时检测算法.     

相干多普勒测风激光雷达低信噪比区域回波信号的估计方法

相干多普勒测风激光雷达通常会采用周期图最大值法（PM）提取不同距离门信号的多普勒频移（对应风速）信息。由于噪声和相干效率的影响,个别距离门信号会出现信噪比（SNR）突然降低的情况,从而导致系统的探测概率降低,影响系统整体的探测性能。为了解决个别距离门信号多普勒频移的错误估计问题,提出了一种新的非线性自适应多普勒频移估计方法。该方法利用风速的连续性,标定错误距离门,并自适应地利用强信噪比区域的多普勒频移统计数据来弥补信噪比变差而出现的估计错误。分别利用了仿真模型和一套1.54μm全光纤相干激光雷达系统获得了风场测量数据,对比了使用该技术前后反演得到的风速趋势,证明该方法能够有效地解决上述问题。     

Modified Algorithm for Calculating the Ambiguity Function in the Problem of Estimating the Mutual Time Delays of Wideband Signals

Radiophysics and Quantum Electronics - Using the modified algorithm for calculating the ambiguity function, we consider the method of estimation of the mutual time delay of wideband signals, which...     

The use of balanced homodyne and squeezed states for detecting weak optical signals in a Michelson interferometer

The possibility of using squeezed states and balanced homodyne detection of optical signals in a Michelson interferometer is discussed. The present analysis describes photon statistics measurements effects related to quadrature balanced homodyne detection showing the advantage of using this scheme for detecting weak optical signals.     

Emergent spin

Quantum mechanics and relativity in the continuum imply the well known spin–statistics connection. However for particles hopping on a lattice, there is no such constraint. If a lattice model yields a relativistic field theory in a continuum limit, this constraint must “emerge” for physical excitations. We discuss a few models where a spin-less fermion hopping on a lattice gives excitations which satisfy the continuum Dirac equation. This includes such well known systems such as graphene and staggered fermions.     

Infrared/laser multi-sensor fusion and tracking based on the multi-scale model

The state estimation problem of targets detected by infrared/laser composite detection system with different sampling rates was studied in this paper. An effective state estimation algorithm based on data fusion is presented. Because sampling rate of infrared detection system is much higher than that of the laser detection system, the theory of multi-scale analysis is used to establish multi-scale model in this algorithm. At the fine scale, angle information provided by infrared detection system is used to estimate the target state through the unscented Kalman filter. It makes full use of the high frequency characteristic of infrared detection system to improve target state estimation accuracy. At the coarse scale, due to the sampling ratio of infrared and laser detection systems is an integer multiple, the angle information can be fused directly with the distance information of laser detection system to determine the target location. The fused information is served as observation, while the converted measurement Kalman filter (CMKF) is used to estimate the target state, which greatly reduces the complexity of filtering process and gets the optimal fusion estimation. The simulation results of tracking a target in 3-D space by infrared and laser detection systems demonstrate that the proposed algorithm in this paper is efficient and can obtain better performance than traditional algorithm.