相参雷达间歇采样灵巧干扰方法

间歇采样转发干扰是针对相参雷达一种有效的干扰方法,它利用脉压雷达匹配滤波特性,能够对雷达形成假目标干扰.首先分析了间歇采样转发干扰方法,指出了间歇采样转发干扰的不足之处,即脉压后干扰能量损失和假目标分布均匀,进而提出了间歇采样灵巧干扰方法,新方法形成的假目标分布不均匀,使得雷达识别真假目标可能性大大降低,仿真实验验证了新干扰方法的有效性.     

尺度自适应特征压缩跟踪

为在复杂环境中对目标进行长时间精确跟踪,提出一种尺度自适应特征压缩跟踪算法。通过结构约束性采样,获取不同尺度不同位置的扫描窗,离线计算不同尺度下的稀疏随机感知矩阵。在线跟踪时利用这些矩阵感知对应尺度的图像采样块,实现特征降维,提高运算速度。利用朴素贝叶斯分类器对降维特征判决,在线学习更新分类器参数,找出具有最高分类得分的采样块作为新的跟踪结果,实现跟踪位置及尺度的自适应更新。实验结果表明,该算法能适应目标的基本姿态变化及尺度缩放,不依赖于目标初始跟踪区域尺度选取,跟踪结果具有较强的鲁棒性。     

软件化雷达的多路超高速ADC数字谱分析

用于软件雷达硬件平台的并行多路等效时间超高速ADC系统中,客观地存在着诸多不可避免的工作非均匀性,如:时基抖动、通道直流偏置不均衡及通道增益不一致等等,而造成取样输出信号的频谱发生畸变,影响雷达系统性能.综合讨论了由于采样非均匀和通道偏置及增益不一致对取样信号数字谱的影响,在矩形抽样和理想抽样情况下,建立了该信号数字频谱的完整数学模型,并以理想抽样的正弦信号为例进行详细分析,得到了采样系统输出信噪比的计算公式,为系统的后续补偿校正,及对软件雷达系统指标的确定与分配提供了参考和依据.     

Sequential and systematic sampling plans for the Markov‐dependent production process

Acceptance sampling plans are used to assess the quality of an ongoing production process, in addition to the lot acceptance. In this paper, we consider sampling inspection plans for monitoring the Markov‐dependent production process. We construct sequential plans that satisfy the usual probability requirements at acceptable quality level and rejectable quality level and, in addition, possess the minimum average sample number under semicurtailed inspection. As these plans result in large sample sizes, especially when the serial correlation is high, we suggest new plans called “systematic sampling plans.” The minimum average sample number systematic plans that satisfy the probability requirements are constructed. Our algorithm uses some simple recurrence relations to compute the required acceptance probabilities. The optimal systematic plans require much smaller sample sizes and acceptance numbers, compared to the sequential plans. However, they need larger production runs to make a decision. Tables for choosing appropriate sequential and systematic plans are provided. The problem of selecting the best systematic sampling plan is also addressed. The operating characteristic curves of some of the sequential and the systematic plans are compared, and are observed to be almost identical. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 451–467, 2001     

罗兰C信号模拟器的设计与实现

运用数控技术产生罗兰C信号 ;通过对罗兰C脉冲的傅立叶分析和采样分析 ,确定仪器所用的采样频率和滤波器 ,给出了设计及实现罗兰C信号模拟器的原理     

高炮防空反导系统有关环节采样频率的分析与优选

从系统的精度、平稳性和硬件造价、计算机负担等方面对高炮防空反导系统中的目标测定器输出采样频率和棱镜伺服系统采样频率的取值进行了理论分析和计算机仿真,在此基础上给出了最佳取值范围。     

采用压缩感知的卫星高频姿态确定方法

高频振荡通常会超过星载陀螺和星敏的测量频率范围,导致卫星姿态确定精度下降。因此,提出一种基于常规姿态传感器进行高频姿态确定的方法。将高频姿态抖动看作一个稀疏信号,通过压缩感知的方法将该信号从低频采样结果中恢复。利用低带宽姿态传感器和卡尔曼滤波器测量得到低频姿态数据并进行融合,再通过压缩感知算法从融合数据中恢复出高频姿态数据。通过仿真实验验证了该方法的有〖BHDWG8,WK10YQ,DK1*2,WK1*2D〗〖XCWP.TIF;%129%129〗听语音 聊科研与作者互动 效性。     

Bayesian sampling plans for exponential distributions with interval censored samples

This article studies the problem of designing Bayesian sampling plans (BSP) with interval censored samples. First, an algorithm for deriving the conventional BSP is proposed. The BSP is shown to possess some monotonicity. Based on the BSP and using the property of monotonicity, a new sampling plan modified by the curtailment procedure is proposed. The resulting curtailed Bayesian sampling plan (CBSP) can reduce the duration time of life test experiment, and it is optimal in the sense that its associated Bayes risk is smaller than the Bayes risk of the BSP if the cost of the duration time of life test experiment is considered. A numerical example to compute the Bayes risks of BSP and CBSP and related quantities is given. Also, a Monte Carlo simulation study is performed to illustrate the performance of the CBSP compared with the BSP. The simulation results demonstrate that our proposed CBSP has better performance because it has smaller risk. The CBSP is recommended. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 604–616, 2015     

基于改进MUSIC算法的宽带频谱快速感知方法

针对宽带频谱感知中采样率大、感知时间长的问题,在调制宽带转换器采样的基础上提出了一种改进多重信号分类算法的宽带频谱快速感知方法。调制宽带转换器对宽带频谱进行欠奈奎斯特采样,以最小描述长度准则估计信号个数,用改进多重信号分类谱估计信号位置。算法引入调整因子,使得多重信号分类谱中信号位置更为明显,降低了噪声的干扰。整个感知过程无需重构原始波形,无需计算频谱,大大降低了计算量,而且感知算法计算复杂度低,提高了感知效率。仿真结果表明,在低信噪比的情况下,该算法仍具有很好的检测性能。     

优化拉丁方试验设计方法及其应用

计算机仿真是复杂系统优化的一种有效手段,但需要耗费大量机时,必须严格限制仿真次数。针对此提出了优化拉丁方试验设计方法,该方法需要较少的仿真次数,且兼顾方案的正交性和均匀性,采用Cholesky分解生成初始解,通过模拟退火算法对拉丁方矩阵进行优化,定义动态权重因子实现正交性与均匀性的权衡。最后构建了一个实例,通过试验结果证明采用优化拉丁方试验设计方法可以生成具有较好性质的仿真方案,且仿真次数少。