采用扩频技术的数字天线跟踪系统设计

在介绍雷达领域传统目标跟踪方式基础上, 设计了一种基于扩频体制并有效融合“模极值捕获跟踪”和“数字导引”的数字天线跟踪系统。通过精心设计通信帧格式,并采用具有良好正交性的PN码（Walsh）序列“携带”GPS信息用于数字导引,使得系统在具有30 dB高同步捕获增益的前提下同时具有可控的扩频抗干扰增益,在初始捕获和抗干扰通信过程中发挥重要作用。系统采用具有快速算法的自适应滤波技术对数字导引信息进行置信度分析。建模仿真与飞行试验表明,该方法相对传统体制具有更高的灵活性和可靠性。     

基于双边滤波的主动轮廓模型细胞图像分割方法研究

区域主动轮廓模型采用先验知识指导建立分割模型,并在分割的过程中采用水平集演化的方式使得零水平集自动收敛于目标物体的边界。在采用该模型进行分割之前,通常都采用高斯滤波器对图像进行滤波,但是高斯滤波器在对物体进行平滑操作的同时,也会造成物体边界的弱化,从而影响分割效果。本文将双边滤波和区域主动轮廓模型结合起来,充分利用双边滤波在平滑目标内部的同时不弱化边界的特点,在利用区域主动轮廓模型进行分割之前使用双边滤波对图像进行处理,实验结果显示使用本方法进行分割得到的结果准确性得到了提高。     

特征选择在协同过滤推荐算法中的应用研究

用户-项目评分数据集的高维稀疏性使得传统的协同过滤处于"维度困境"。运用降维技术的特征变换方法的协同过滤算法虽然缩减用户-项目评分数据集规模,但在某种程度上导致信息损失。本文提出将特征选择方法和技术运用于协同过滤算法,并且给出了基于有监督特征选择的协同过滤框架及其协同过滤流程。     

基于双通道接收的干扰对消性能分析

为了探究在工程实现中卫星通信地球站使用干扰对消抵抗来自空中平台或周边干扰的可行性,对不同接收环境下的干扰对消性能进行了分析。首先,在假定2个通道中干扰差异被准确估计并补偿的情况下,推导出理论性能的近似计算公式;然后,采用最小均方(least mean square, LMS)自适应滤波器对2个通道干扰的差异进行补偿,完成干扰对消;最后,通过仿真实验对使用LMS自适应滤波器的干扰对消进行验证。结果表明：干扰对消的理论性能在卫星信号与干扰入射夹角大于15°时信噪比恶化可以接近0 dB,而夹角小于15°时信噪比恶化程度明显提高;除了入射夹角的影响外,采用LMS自适应滤波器的干扰对消性能还受算法参数、干扰大小等其他因素的影响,对于固定频点的干扰,在入射夹角大于4°且主通道干信比小于30 dB时,干扰对消后信噪比恶化小于0.6 dB,而且这一结果基本不受采样率的影响。所提出的理论性能近似计算公式可以为干扰对消算法的性能评价提供参考,采用LMS自适应滤波器的干扰对消在算法参数设置合理的情况下可以接近理论性能。     

Scalable Bayesian Multiple Changepoint Detection via Auxiliary Uniformisation

In this paper, we perform a sparse filtering recursion for efficient changepoint detection for discrete-time observations. We attach auxiliary event times to the chronologically ordered observations and formulate multiple changepoint problems of discrete-time observations into continuous-time observations. Ideally, both the computational and memory costs of the proposed auxiliary uniformisation forward-filtering backward-sampling algorithm can be quadratically scaled down to the number of changepoints instead of the number of observations, which would otherwise be prohibitive for a long sequence of observations. To avoid model bias, a time-varying changepoint recurrence rate across different segments is assumed to characterise diverse scales of run lengths of the changepoints. We demonstrate the methods through simulation studies and real data analysis.     

宽带信号数字信道化及跨信道重构侦测技术

针对在无源探测大带宽信号的过程中会产生跨信道失真问题，提出了一种跨信道可重构的信道化方法。首先经过均匀滤波器组粗滤波，再引入检测时间自适应的双门限能量检测机制，对粗滤波信号进行跨信道判决，之后对各个跨信道信号分别进行可重构信道化设计，从而恢复出原始信号。与传统的数字信道化方法相比，该算法能够更新能量检测门限对跨信道信号进行实时判决，对跨信道信号的重构准确率高于98.3%，实现了对跨子信道带宽信号的近似无失真重构。Matlab仿真结果验证了算法的有效性。     

High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange

Intraday correlation dynamics poses challenges to financial econometricians, especially in recently popular high frequency domain, due to non-synchronous trading and market microstructure noise. Traditional models fail to address the issues inherent to the nature of the data, which is riddled with noisy signals and missing values. We employ a recently developed method based on Generalized Autoregressive Score (GAS) framework and State-Space Modeling to remedy these characteristics of high frequency data and estimate intraday correlations in Turkish equity market Borsa Istanbul. Our findings reveal that average intraday conditional correlation rises as trading commences and lingers around certain altitude for some time, with the eigenvalues associated with market factor becoming progressively more dominant. An upward trend closes out the trading day on Mondays, which we attribute to the US market opening, whereas the rest of the week does not show a generalizable closing-time effect. Assessment of the findings across different market conditions and days of the week reveals elevated correlation levels in volatile markets as well as a distinguishable path for the beginning of the week. Beyond the scholarly contribution, the methodology can be used as a nowcasting tool and the findings are of interest to various parties like high-frequency traders, risk and portfolio managers and regulatory agencies in formulating their high frequency trading practices, hedging, portfolio construction schemes and margin requirements, respectively.     

基于WEB挖掘的虚拟企业合作伙伴选择研究

将基于WEB的文本挖掘应用到虚拟企业合作伙伴选择过程中,通过已有的网页搜集、文本过滤、信息抽取等相关文本处理技术自动提取Internet上企业的相关信息,从而为核心企业提供大量的潜在伙伴信息,缩短虚拟企业组建时间,提高核心企业市场反应速度。     

利用Kalman滤波修正卫星导航差分RTK定位坐标

卫星导航差分RTK(Real Time Kinematic)定位方法的定位精度极易受到载波相位整周模糊度固定算法的影响，在模糊度固定失败的情况下，差分RTK定位将出现大幅偏差。针对该问题，基于Jerk模型提出了一种利用Kalman滤波修正差分RTK定位坐标的方法。在传统Jerk模型基础上，将卫星导航系统输出的载体运动速度信息引入状态空间模型的观测方程。基于扩展状态空间模型，利用Kalman滤波器实时修正载体的位置坐标。半实物仿真表明，所提方法能大幅改善卫星导航差分RTK定位精度。