在量化阵列框架下的对称Alpha稳定信号检测的预处理方法

本文主要研究了淹没在对称α稳态噪声下的信号相关检测的最优和次优的预测处理方法。使用量化阵列模型的等价处理函数和对相关运算的高斯近似，通过最大化相关器的输出信噪比，建立了约束泛函优化问题。由于量化阵列的泛函优化问题很难得到解析解，本文将预处理函数离散化，并证明离散后的优化问题是凸二次规划问题，从而可通过凸优化的方法求解。本文提出了一种基于排序方法的自适应门限的软限幅检测器，相比现有的检测器，仅仅需要估计噪声参数α。仿真结果表明，提出的量化阵列系统等价的预处理函数逼近最大似然检测器，提出的软限幅检测器达到了近似最优的性能，有利于实时处理α稳态信号。      

阵列双稳随机共振在微弱信号检测中的应用研究

阵列双稳随机共振(stochastic resonance, SR)系统可利用噪声在单个双稳SR系统基础上进一步增强微弱信号检测的能力,为强噪声背景下微弱信号的检测开创了新方法。本文应用阵列双稳SR原理进行微弱信号检测的研究,采用理论和数值仿真相结合,通过稳态自协方差函数,分析了阵列双稳SR系统输出信噪比（signal-to-noise ratio, SNR）增益。在此基础上,分别讨论了阵列噪声、外部噪声及阵列单元数对检测性能的影响。并与单个双稳SR检测弱信号进行性能比较,分析和仿真结果都表明,在相同条件下,采用阵列双稳SR比采用单个双稳SR检测微弱信号性能有较大改善。这些研究结果对于阵列双稳SR的进一步发展及应用具有重要意义。      

极化敏感阵列信号检测:部分极化情形

首次深入研究了基于极化敏感阵列的部分极化信号检测问题.建立了部分极化信号检测模型;在高斯分布假设条件下,利用矩阵特征分解求得似然比统计检验量,并给出了最优检测器的结构框图;推导求得统计检验量的概率密度函数,根据N-P准则求得检测器的检测性能;进一步利用上述理论结果分析了结构噪声背景下检测器的检测性能,分析了信号极化度、干扰强度、干扰极化度以及干扰到达角等因素对检测器检测性能的影响.     

异步DS-CDMA系统中的最优时空线性多用户检测器

该文给出了一种适用于异步DS-CDMA系统的通用线性时空二维多用户检测方法,它将所有线性多用户检测器归结到一个统一的数学模型之下。基于此模型,该文将时空线性多用户检测问题转化为一个权矢量的优化问题,并在线性约束最小方差(LCMV)准则下给出了权矢量的优化解。对现有的几种典型线性多用户检测器的分析表明,这些方法都可以看作是该文提出的通用时空线性多用户检测方法的特例,且只能在某种限定条件下得到局部最优解,因此其抑制多址干扰和噪声的能力都低于文中的最优时空线性多用户检测器。最后,给出了数值仿真结果。     

同步DS-CDMA系统中的最优时空线性多用户检测器

本文给出了一种通用的时空二维线性多用户检测方法,它将所有线性多用户检测器归结到一个统一的数学模型之下.基于此模型,本文将时空线性多用户检测问题转化为一个权矢量的优化问题,并在线性约束最小方差(LCMV)准则下给出了权矢量的优化解.对现有的几种典型的线性多用户检测器的分析表明,这些方法都可以看作是本文提出的通用时空二维线性多用户检测方法的特例,且只能在某种限定条件下得到局部最优解,其抑制多址干扰和噪声的能力都低于文中的最优时空线性多用户检测器.最后,本文给出了数值仿真结果.     

基于随机Hopfield神经网络的最优多用户检测器

Hopfield神经网络检测器与传统检测器相比具有独特的魅力,但存在局部收敛问题.随机Hopfield神经网络通过对状态变量引入噪声,从而避免局部收敛,进而达到最优检测.本文给出了CDMA移动通信系统中基于随机Hopfield神经网络的最优多用户检测器的统一框架,该检测器利用随机Hopfield神经网络对最大似然函数进行优化从而得到最优检测性能.在三种典型信道中对这些检测器性能进行比较,结果表明该检测器比传统检测器的性能更好.     

H.264中基于人脸检测的分级量化

针对H.264视频标准在视频会议等以人物为主体的视频应用,设计了一种基于人脸检测的分级量化器,文章首先介绍了H.264标准的量化基本原理,然后给出了结合人脸检测的分级量化器的设计,实验证明该量化器能够更有效地压缩图像.     

基于信息几何理论的信号检测方法

信息几何理论将统计推断问题转换为几何问题进行处理,从而能够从几何的角度分析进行统计推断。以高斯噪声下的信号检测为研究对象,给出了基于信息几何理论的信号检测所需的理论基础,分析了测地线距离与检测器性能之间的关系。分别以简单假设和复合假设两种情况,分析了两种距离检测器的性能,并与Neyman-Pearson检测器和广义似然比检测器进行了对比。计算机分析结果表明,测地线长度和方向共同决定了检测性能,且距离检测器性能与似然比检测器性能相当。     

基于Fisher线性判别的多用户检测器

本文提出一种基于Fisher线性判别(FLD)的多用户检测器。该检测器将信道的时变特性隐含在学习算法得出的最优投影方向矢量中,因而适合各种信道环境,而不必知道噪声和干扰的类型;它需要训练序列,除了有用信号的扩频序列外,不需要其他用户的扩频序列;算法简单、实现复杂度低。本文对所提出的检测器性能进行了仿真实验,给出了FLD检测器与MMSE检测器和SVM检测器的性能比较。     

色噪声下共址MIMO雷达自适应检测波形设计

研究了存在色噪声时共址MIMO雷达的自适应检测波形设计问题.推导了检测率、虚警率与发射波形关系的表达式.鉴于该表达式的复杂性,引入两个渐近准则,即相对熵和散度准则,同时推导了最优检测波形的闭式解.经理论分析和实验仿真得出结论:两种信息论准则对应的最优波形是一致的;最优检测波形与目标、噪声匹配;最优检测波形的信噪比同时也达到最优.     

Multiuser square-law detection with applications to fiber optic communications

Optimal and suboptimal multiuser noncoherent detection for square-law receivers is studied in this paper. Great potential is found for the multiuser square-law detector when compared with the conventional single-user square-law detector. We study the optimal detector and two detectors with simpler structures: the asymptotically optimal detector and the pairwise linear detector. The saddle-point approximation method is used to study the error performance and its asymptotic behavior as noise reduces. Due to difficulty in optimizing the detectors at an arbitrary noise level, we propose to use the asymptotic efficiency for detector optimization. For a low-error-rate system like a fiber optic communication system, the asymptotic efficiency is found to be an efficient way to design detectors. Numerical results show that the asymptotically optimized detectors perform as well as the optimal detector, even for nonzero noise levels of practical interest. Despite their exponential complexity, these detectors are applicable to wavelength-division multiplexed systems in which only a few neighboring channels produce strong interference.     

Estimation of noisy telegraph processes: Nonlinear filtering versus nonlinear smoothing (Corresp.)

In the estimation problem of a two-state stationary Markov process with Gaussian white noise added, the optimal smoother is a two-filter smoother. In a special case, the performance of the optimal nonlinear filter and smoother is evaluated analytically. Some asymptotic results are also derived.     

像素感光面形状对基于微扫描的红外超分辨成像的影响

基于微扫描的超分辨成像技术在成像系统光学参数不变的基础上提高图像分辨率,常用于红外成像领域。目前,在基于微扫描的红外超分辨成像研究中,采用理想的正方形模型来仿真红外探测器的感光面形状。但是,由于读出电路的存在,实际探测器产品中像素感光面形状并非严格的正方形,使用正方形模型仿真会导致仿真结果和研究结论的不准确。推导了长方形和折形两种感光面模型对成像的影响,并通过与正方形模型的仿真对比确定相应的误差,最后结合实验对前述研究成果进行了验证。结果表明:极限情况下,相对于折形模型,使用方形模型仿真的误差高达41%;相同像素填充率时,折形感光面越远离中心,对成像的MTF影响越大;基于探测器真实感光面形状的仿真模型能有效提高对红外超分辨成像研究的准确性。     

Stochastic Resonance in Sequential Detectors

Stochastic resonance (SR) is a nonlinear phenomenon known in physics that has attracted recent interest in the signal-processing literature, and specifically in the context of detection. We investigate the SR effect arising in sequential detectors for shift-in-mean binary hypothesis testing and characterize the optimal resonance as the solution of specific optimization problems. One particular (and at first glance perhaps counterintuitive) finding is that certain sequential detection procedures can be made more efficient by randomly adding or subtracting a suitable constant value to the data at the input of the detector.     

Memoryless discrete-time detection of a constant signal in m-dependent noise

The problem of designing memoryless detectors for known signals in stationary m-dependent noise processes is considered. Applying the criterion of asymptotic relative efficiency, the optimal such detector is shown to be characterized by the solution to a Fredholm integral equation whose kernel depends only on the second-order probability distributions of the noise. General expressions are derived for this solution and for the asymptotic efficiency of the optimal detector relative to other memoryless detectors. To illustrate the analysis, specific results are given for the particular case where the noise process is derived by memoryless nonlinear transformation of a Gaussian process. In addition, an extension of the analytical results to the more general case ofphi-mixing noise processes is discussed.     

On sequential sign detection of a constant signal

In fixed sample size signal detection, the sign detector is easier to implement and requires much less knowledge of the noise density than does the optimum fixed sample size detector. These advantages accrue at a cost of more observations needed to achieve the same performance. By utilizing the sign detector sequentially, it is shown that considerable saving in the (average) number of observations is obtained over the corresponding optimal fixed sample size detector. The asymptotic relative efficiencies, as the signal-to-noise ratio and both probabilities of error approach zero, of the sequential sign detector compared to fixed sample size detectors are derived. The possibility of truncating the test to avoid excessively large numbers of observations is considered.     

液氮制冷的AlGaN/GaN HEMT太赫兹探测器阵列特性研究

为充分发挥AlGaN/GaN高电子迁移率晶体管 (High-Electron-Mobility Transistor, HEMT)太赫兹探测器阵列的高电子迁移率优势,文中研究了HEMT太赫兹探测器阵列在77 K下的探测特性。使用液氮杜瓦为降温主体搭建了适用于焦平面 (Focal-Plane Array, FPA)芯片的低温系统,实现了对焦平面芯片常温与低温下的对比测试。温度从300 K降到77 K时,探测器阵列像元的平均响应度提高近3倍,平均噪声有小幅增大,340 GHz时平均噪声等效功率 (Noise Equivalent Power, NEP)从45.1 pW/Hz1/2降低到了19.4 pW/Hz1/2,灵敏度提高两倍以上。与硅透镜耦合的单元探测器相比,阵列像元的灵敏度提升仍有较大空间。主要是由于各像素点最佳工作电压的不一致,导致在给定统一工作电压下像元间的响应度和噪声都表现出较大的离散性,文中讨论了降低最佳工作电压离散度的可能解决方案。     

Noncoherent multiuser detection for nonlinear modulation over the Rayleigh-fading channel

The jointly optimum noncoherent multiuser detector is obtained for nonlinear nonorthogonal modulation over the frequency nonselective Rayleigh-fading multiple-access channel. Upper and lower bounds on the average bit-error probability are derived. While these bounds are numerically computable, they are too complicated to give insight into the relative influence of the system parameters on the essential behavior of the bit-error rate. Hence this paper develops an asymptotic analysis of the average bit-error probability. In particular, it is shown that the upper and lower bounds are asymptotically convergent. An exact formula for the asymptotic efficiency of the optimum noncoherent detector is derived. Interestingly, the asymptotic efficiency is found to be positive and independent of the signal strengths of the interfering users. In contrast, the noncoherent detector which would be optimal in a single-user channel (the "conventional detector"), when used over the multiuser channel, has an asymptotic efficiency that is identically equal to zero no matter what the powers of the interferers may be. While the performance analysis of the optimum detector provides the fundamental limit on achievable error rate, the implementational complexity of the optimum detector is exponential in the number of users. As a low-complexity alternative, a decorrelative energy detector is also proposed and analyzed in terms of error probability and asymptotic efficiency.     

Reducing the Sampling Complexity of Energy Detection in Cognitive Radio Networks under Low SNR by Using the Optimal Stochastic Resonance Technique

We propose a novel noncooperative technique in cognitive radio (CR) networks, which is based on the optimal stochastic resonance (SR) technique. By introducing the dynamic system approach of SR into the noncooperative spectrum sensing process, the defect of high sampling complexity of traditional energy detector can be reduced efficiently and thus can guarantee the applicability of the optimal SR-based energy detection method. The optimization of the signal-to-noise ratio (SNR) improvement of the system ensures the lowest sampling complexity needed to reach certain performance requirement. Computer simulations show that it can reduce the sampling complexity compared with traditional energy detector used in IEEE 802.22 draft especially under low SNR environments. It can certainly be extended to other wide application areas.     

Approximation of locally optimum detector nonlinearities (Corresp.)

The problem of finding a detector nonlinearity that maximizes the efficacy (or asymptotic processing gain) over a class of suboptimal nonlinearities is considered. It is shown that this efficacy maximization problem is essentially the same as the problem of finding the minimum-mean-square-error approximation to the locally optimal detector nonlinearity. This result is compared with some intuitive ideas about suboptimal detection.