GPS接收机伪码捕获自适应判决门限估计算法(英文)

GPS接收机输入信号的功率随时间而变化,如果采用固定门限判决是否完成捕获会出现检测概率降低或虚警概率提高的问题.鉴于此,提出了采用自适应捕获门限判决策略完成信号捕获.采用最大似然估计原理,根据判决统计量的样本值得到了噪声方差的最大似然估计,进而求得恒虚警率下的自适应捕获门限.同时,信号的平均捕获时间是GPS接收机性能的重要指标之一,研究了载波频率与伪码相位均为不确定值时的平均捕获时间的计算方法,推导了平均捕获时间与信噪比及门限值之间的约束关系.分析结果表明,自适应门限捕获方法能减小平均捕获时间,实现信号的快速捕获.     

谱差法在线谱引信技术中的应用

介绍了谱差法的原理,导出了自动检测门限,讨论了实际应用中存在的问题。仿真结果表明谱差法可提高信噪比,降低虚警率,增强检测可靠性。     

认知无线电系统的动态双门限协作能量检测算法

认知无线电系统中,认知用户间协作检测有利于提高频谱检测的准确性。基于OR(或)协作方式和多门限能量检测算法,提出了一种动态双门限协作能量检测算法,并根据认知用户接收到的主用户信噪比确定检测门限。理论分析和仿真结果表明,该算法可以有效提高频谱检测概率,降低系统漏检概率。     

基于慢度估计的次声台阵信号自动检测算法及应用

针对次声监测研究领域广泛使用的短时间与长时间信号功率比检测方法性能不能满足要求,渐进多通道互相关检测算法虚警率较高的缺点,利用信号的时、频、波数域特性和次声台阵各子台信号的互相关性特性,提出了一种基于次声台阵信号慢度估计的自动检测算法。次声信号慢度估计结果的合理性、一致性是该检测算法的依据。考虑到该检测算法计算量较大,在具体应用中加入其他计算量较小的传统算法,进行逐次检测,最后应用的慢度估计方法既是一种检测方法,也是对其他检测算法结果的最终审核,一方面可以降低单项检测方法对检测参数的敏感性,另一方面也可提高检测的正确率(虚警率和漏警率同时降低)。该复合检测算法应用于某实验次声台站信号的检测(信噪比大于1.1),结果虚警率为4.0%,漏警率为5.0%,表明了该方法的优良性能。从检测应用处理结果还可以推测,结合一个区域现有密集的地震台站数据和2~3个次声台阵的数据,可以方便地识别、监控爆破方式日益复杂的人工爆破事件和真正的地震(余震)事件,为地震灾害减灾防灾、采矿监控等多领域服务,具有重大推广价值。     

光电图像序列运动弱目标实时检测算法

针对光电探测图像序列中的运动弱小目标实时检测问题,提出了一种基于时空域融合滤波的弱目标检测算法。算法在空域上利用形态学Tophat滤波抑制背景增强目标,在时域上通过改进的帧间差分方法增强运动目标,两者融合后经自适应门限分割与航迹关联确认目标。实际录取数据分析结果表明,算法全面考虑运动弱小目标在时域与空域方面的特性,能更有效地从复杂背景中检测低信噪比运动弱小目标,减小了虚警率,抗噪声干扰能力强。     

低频脉冲信号的频域恒虚警检测

为提高低频背景噪声中弱声呐脉冲信号的检测能力,给出了一种频域恒虚警检测方法。该方法针对低频背景噪声平稳性较差、起伏较大的特点,将频域中峰值点或极值点认为是疑似脉冲信号,通过对疑似点能量与历史背景进行比对的方式完成脉冲信号的检测判决,并且给出了相应的检验统计量获取方法、背景噪声估计方法和恒虚警检测门限的计算方法。仿真分析和实际数据处理结果表明,频域恒虚警检测方法对单频脉冲、单频-线性调频组合脉冲等包含窄带成分的弱声呐脉冲信号有非常好的检测性能。     

空间交会对接低信噪比标志捕获技术研究

针对近距离空间交会对接低信噪比情况下标志灯像点的识别，提出了一种基于多帧高阶互相关和最大似然比检测的标志捕获技术。首先通过单帧自适应门限检测和两次高阶互相关处理抑制大量随机噪声，然后利用最大似然比检测自适应算法从候选轨迹中剔除大部分虚假轨迹，最后通过特殊设计的后处理操作进一步剔除残留的干扰轨迹，识别出真正的目标轨迹。实验表明，可识别的最低信噪比为0．5。     

脉冲宽度检测器用于降低虚警率

一、引 言 声纳信号处理的基本目的是尽量增大声纳信号的输出信噪比,提高信号检测概率,同时减小虚警率,提高检测信号的可信度。声纳信号接收机通常利用干扰信号与有用信号在频谱和能量上的差别,采用滤波和设置门限判决电路的方法来抑制干扰信号,检测出有用信号。     

一种高速目标检测算法研究及实现

为了实时有效的实现雷达跟踪高速运动目标检测,研究了小波检测器的算法和硬件实现。小波检测器的快速算法并对其作了优化设计构成检测系统的软件基础,采用ADSP21160DSP芯片开发出恒虚警检测并行处理系统。仿真结果和检测性能分析表明,该系统能有效检测低信噪比下高速运动目标,并且有很好的实时性。     

基于分层动态规划的红外弱小目标检测

为了检测低信噪比下的红外弱小目标,本文将方向中值滤波与分层动态规划算法相结合进行检测前跟踪。利用背景杂波在局部空间上的相关性,提取目标在四个方向的中值进行自适应加权滤波,抑制结构性杂波分量,改善信噪比。针对分割后的备选目标点,为了减少跟踪检测的计算量,根据真实目标运动轨迹的连续性与光滑性,利用分层动态规划算法进行多帧检测,进而对多层检测结果进行配准并做出决策。仿真实验表明方向中值滤波有效的提高了信噪比,分层动态规划算法进一步降低了虚警概率,同时大大提升了计算速度。     

Intermittent failure process and false alarm interaction modelling of threshold-based monitoring built-in tests (BITs)

Built-in tests (BITs) are widely used in manufacturing and production systems to find whether system failures occur, whereas the problem of BIT false alarms caused by intermittent failures adds to much trouble for the precise failure detection and diagnosis. Fighting with false alarms caused by intermittent failures is an urgent issue. However, the nature and temporal regularity of intermittent failures are not fully exploited, as well as the relationship between intermittent failure and BIT false alarms. The present paper introduces the method of constructing failure test profile for false alarm assessments. Probabilistic models are proposed of the failure evolution process, as well as the interactions between intermittent failures and false alarms. The false alarm time expectation is derived with the given model, serving as the foundation for the optimisation problem to find the best test threshold to enable the highest BIT capability. A numerical analysis is made to illustrate the proposed model and examine the threshold determination method. An application study is also carried out to show how the model can be applicable in real engineering practices.     

Improved probabilistic neural network algorithm for chemical sensor array pattern recognition

An improved probabilistic neural network (IPNN) algorithm for use in chemical sensor array pattern recognition applications is described. The IPNN is based on a modified probabilistic neural network (PNN) with three innovations designed to reduce the computational and memory requirements, to speed training, and to decrease the false alarm rate. The utility of this new approach is illustrated with the use of four data sets extracted from simulated and laboratory-collected surface acoustic wave sensor array data. A competitive learning strategy, based on a learning vector quantization neural network, is shown to reduce the storage and computation requirements. The IPNN hidden layer requires only a fraction of the storage space of a conventional PNN. A simple distance-based calculation is reported to approximate the optimal kernel width of a PNN. This calculation is found to decrease the training time and requires no user input. A general procedure for selecting the optimal rejection threshold for a PNN-based algorithm using Monte Carlo simulations is also demonstrated. This outlier rejection strategy is implemented for an IPNN classifier and found to reject ambiguous patterns, thereby decreasing the potential for false alarms.     

一种低成本高性能的巡逻保安机器人

为满足在办公室、仓库等建筑内巡逻的要求,研制了一种低成本、高性能的巡逻保安机器人.其传感器系统采用分层模糊理论,能够在比较复杂的情况下完成自主导航和障碍避碰等任务.火灾探测系统采用神经网络和灰色预测理论,提高了报警的灵敏度,减少了误报警,缩短了报警时间.无线通讯的方式更适合于网络监控和远程操纵.实验证明,该巡逻保安机器人具有低成本、高性能的特点,具有较高的性价比,适合办公室、仓库、厂房等环境的巡逻与监控.     

Performance study of change-point detection thresholds for cumulative sum statistic in a sequential context

Sequential detection is based on a recursive statistic and a threshold it must reach to report a change. In this paper, we consider the score-based cumulative sum statistic and propose to evaluate the detection performance of some thresholds on simulated data. Three thresholds come from the literature: the Wald constant, the empirical constant, and the conditional empirical instantaneous threshold (the latter two are built by a simulation-based procedure). Two new thresholds are built by a simulation-based procedure: the first one is instantaneous, the second is a dynamical version of the previous one. The thresholds' performance measured by an estimation of the mean time between false alarm (MTBFA) and the average detection delay (ADD) are evaluated on independent and autocorrelated data for several scenario, according to the detection objective and the real change in the data. The simulations allow us to compare the difference between the thresholds' results and to see that their performances prove to be robust when a parameter of the prechange regime is misestimated or when the data independence assumption is violated. We found also that the conditional empirical threshold is the best at minimizing the detection delay while maintaining the given false alarm rate. However, on real data, we suggest to use the dynamic instantaneous threshold because it is the easiest to build for practical implementation.     

Dynamic probability control limits for CUSUM charts for monitoring proportions with time-varying sample sizes

We consider the problem of monitoring a proportion with time-varying sample sizes. Control charts are generally designed by assuming a fixed sample size or a priori knowledge of a sample size probability distribution. Sometimes, it is not possible to know, or accurately estimate, a sample size distribution or the distribution may change over time. An improper assumption for the sample size distribution could lead to undesirable performance of the control chart. To handle this problem, we propose the use of dynamic probability control limits (DPCLs) which are determined successively as the sample sizes become known. The method is based on keeping the conditional probability of a false alarm at a predetermined level given that there has not been any earlier false alarm. The control limits dynamically change, and the in-control performance of the chart can be controlled at the desired level for any sequence of sample sizes. The simulation results support this result showing that there is no need for any assumption of a sample size distribution with the use of this proposed approach.     

Forty-Sixth Annual Exhibition of the Institute of Physics and the Physical Society

Abstract

The frequency histogram of connected elements (FHCE) is a recently proposed algorithm that has successfully been applied in various medical image segmentation tasks. The FHCE is based on the idea that most pixels belong to the same class as their neighbouring pixels. However, the FHCE performance relies to a great extent on the optimal selection of a threshold parameter. Since evaluating segmentation results is a highly subjective process, a collection of threshold values must typically be examined. No algorithm has been proposed to automate the determination of the threshold parameter value of the FHCE. This study presents a method based on the fuzzy C-means clustering algorithm, designed to automatically generate optimal threshold values for the FHCE. This new approach was applied as a part of a structured sequence of image processing steps in order to facilitate segmentation of microcalcifications in digitized mammograms. A unique threshold value was generated for each mammogram, taking into account the different grey-level patterns based on different compositions of various breast tissues in it. The segmentation algorithm was tested on 100 mammograms (50 collected from the Mammographic Image Analysis Society and 50 normal mammograms onto which a number of simulated microcalcifications were generated). The algorithm was able to detect subtle microcalcifications with sensitivity ranging from 93 to 98%, False alarm ratio from 3 to 5% and false negatives variability from 2 to 3%.     

基于EEMD和分层阈值的磁记忆信号降噪方法研究

针对现有缺陷管道的磁记忆信号降噪效果不佳及信号完整性鲜有考虑等问题,提出了基于总体平均经验模态分解（ensemble empirical mode decomposition,EEMD）和分层阈值的磁记忆信号降噪方法。首先,设计了以STM32F407为控制核心的金属磁记忆检测系统,用于采集缺陷管道的磁信号;然后,对磁信号进行EEMD预处理,得到其本征模函数（intrinsic mode function, IMF）分量,并根据频谱分析和相似度计算选择最佳分解层数;最后,利用分层阈值降噪算法重构在最佳分解层数下的IMF分量,得到降噪后的信号。通过仿真分析和实验测试,对EEMD分层阈值降噪方法进行定量评价。结果表明：该方法适用于信噪比较小的含噪信号;与小波阈值降噪方法相比,其降噪后信号的信噪比和平滑度较高,均方根误差较小,缺陷特征信号完整,可更直观地显示缺陷位置。研究结果为金属管道磁信号降噪提供了一种切实可行的方法,为管道缺陷的在线检测奠定了基础。     

Minimization of the optical smoke detector false alarm probabilityby optimizing its frequency characteristic

The exclusive use of the time domain analysis in the design tuning to lower the probability of false alarms is caused by the output signal binary nature prevailing in the optical smoke detector designs. However, the characteristic of a standard detector circuit is fairly linear up to the output comparator. On the basis of the generalized functional block scheme, for this linear dependence the Laplace transform is derived in this paper. The transfer function obtained is optimized with respect to false alarm probability minimization, for the second and the fourth order cases. Exploiting the optimization results presented, the improvement of the detector design to obtain lower probability of false alarm reduces to the calculation of element parameters from the coefficients of the optimized transfer function. If the requests for detector time response behavior are different from those adopted here, this paper presents a systematic set of design steps that have to be performed to obtain the optimal performance     

Cumulative detection probabilities and range accuracy of a pulsed Geiger-mode avalanche photodiode laser ranging system

Cumulative pulses detection with appropriate cumulative pulses number and threshold has the ability to improve the detection performance of the pulsed laser ranging system with GM-APD. In this paper, based on Poisson statistics and multi-pulses cumulative process, the cumulative detection probabilities and their influence factors are investigated. With the normalized probability distribution of each time bin, the theoretical model of the range accuracy and precision is established, and the factors limiting the range accuracy and precision are discussed. The results show that the cumulative pulses detection can produce higher target detection probability and lower false alarm probability. However, for a heavy noise level and extremely weak echo intensity, the false alarm suppression performance of the cumulative pulses detection deteriorates quickly. The range accuracy and precision is another important parameter evaluating the detection performance, the echo intensity and pulse width are main influence factors on the range accuracy and precision, and higher range accuracy and precision is acquired with stronger echo intensity and narrower echo pulse width, for 5-ns echo pulse width, when the echo intensity is larger than 10, the range accuracy and precision lower than 7.5 cm can be achieved.