基于噪声缩放的自适应UKF-SLAM算法

针对扩展卡尔曼滤波(EKF)算法在移动机器人同时定位和环境建模(SLAM)中的缺点,即非线性系统简单线性化所导致的系统状态方程的不准确性、雅克比矩阵的计算所导致的计算复杂化以及噪声模型不确定性所导致的滤波稳定性降低等问题,提出一种对噪声自适应的UKF-SLAM算法。该算法通过对噪声缩放进而改变噪声模型,利用观测残差序列准确估计观测噪声模型协方差,运用预测的新息协方差和IAE开窗法求其系统状态噪声缩放因子,从而准确估计系统状态噪声模型协方差,实现对不确定的噪声模型能够自适应UKF-SLAM算法。UKF的Sigma点采样策略是比例对称采样。实验结果证明,该方法相对EKF算法和UKF算法具有较高的定位精度和自适应能力。     

利用改进开窗转换法确定沥青离散松弛时间谱

为了精确地获得沥青胶结料的离散松弛时间谱,提出了一种改进开窗转换法的线性黏弹性材料函数转换算法．此方法可以用于离散延迟时间谱和离散松弛时间谱的相互转换．与开窗转换法相比,改进开窗转换法对于时间常数的设置更加精确,并且不会产生负数谱线．将改进开窗转换法用于一种传统非改性沥青的弯曲梁流变仪试验数据的离散延迟时间谱的转换,成功地确定了相应的离散松弛时间谱．经有限元模型验证表明,此离散松弛时间谱能很好地还原该沥青结合料的应力松弛特性．     

Using space windowing for a preliminary analysis of complex time data in human component system studies. Examples with eye-tracking in advertising and car/head movements in driving

Empirical studies of human systems often involve recording multidimensional signals because the system components may require physical measurements (e.g., temperature, pressure, body movements and/or movements in the environment) and physiological measurements (e.g., electromyography or electrocardiography). Analysis of such data becomes complex if both the multifactor aspect and the multivariate aspect are retained. Three examples are used to illustrate the role of fuzzy space windowing and the large number of data analysis paths. The first example is a classic simulated data set found in the literature, which we use to compare several data analysis paths generated with principal component analysis and multiple correspondence analysis with crisp and fuzzy windowing. The second example involves eye-tracking data based on advertising, with a focus on the case of one category variable, but with the possibility of several space windowing models and time entities. The third example concerns car and head movement data from a driving vigilance study, with a focus on the case involving several quantitative variables. The notions of analysis path multiplicity and information are discussed both from a general perspective and in terms of our two real examples.     

MB-OFDM UWB系统中的加窗算法设计

提出一种能抵抗超宽带系统中强窄带干扰的接收端加窗算法,它适用于多带正交频分复用(MB-OFDM)超宽带通信系统中采用的零值填充机制。相对于其他抗窄带干扰算法,接收端加窗算法具有算法复杂度低、无须对窄带干扰进行预估计等优点。在不同强窄带干扰源下的系统无线数据包错误率的仿真测试验证了该算法的有效性和可行性。     

一种改进的导航信号窄带干扰抑制方法

针对导航信号中的窄带干扰问题,提出一种基于频域处理的最小均方(LMS)窄带干扰抑制方法。该方法在传统的LMS滤波器结构中引入权值泄漏因子a,以减少导航信号中有用信号在滤波过程中的损失。通过采用权值系数稳定度d的判断处理去除导航信号中的变频窄带干扰。仿真结果表明,该方法对固频和变频的窄带干扰都有较好的抑制效果,可提高导航接收机的抗干扰性能。     

The use of energy windowing to discriminate SNM from NORM in radiation portal monitors

Energy windowing is an algorithmic alarm method that can be applied to plastic scintillator-based radiation portal monitor (RPM) systems to improve operational sensitivity to certain threat sources while reducing the alarm rates from naturally occurring radioactive material. Various implementations of energy windowing have been tested and documented by industry and at Pacific Northwest National Laboratory, and are available in commercial RPMs built by several manufacturers. Moreover, energy windowing is being used in many deployed RPMs to reduce nuisance alarms and improve operational sensitivity during the screening of cargo. This paper describes energy windowing algorithms and demonstrates how these algorithms succeed when applied to “controlled” experimental measurements and “real world” vehicle traffic data.     

椭圆曲线标量乘的快速实现

提出一种计算固定基点标量乘的快速实现算法，该算法的计算速度明显快于Fixed-base Windowing算法；且当预计算量小于255时，计算速度稍快于Fixed-base Comb算法。而且，该算法可以灵活地改变计算时间和占用内存的大小来适应不同的应用环境。     

关于滑动DFT算法中的频谱泄漏问题的探讨

针对滑动DFT算法中的频谱泄漏效应的处理问题,提出用频域加窗的办法,避免了时域加窗中窗与输入信号的N次相乘,破坏滑动DFT实时计算的简捷性、可靠性,保证了滑动DFT算法的实现与优化。在硬件实现上,用3个结构简单的谐振器,将其谐振频率分别调到3个相邻的DFT频率单元,即可实现此处理过程。     

FFT在低功率微程序控制器中的应用

低功率微处理器的储存空间比较小,如何用其实现FFT变换一直是一个比较重要且很难实现的问题。详细介绍了实现FFT的具体算法包括低功率微处理器的固有缺点,采集样本需要注意的问题及其程序实现,加窗程序以及在实现过程中应注意的问题。在低功率微处理器中实现了FFT变换,结果表明所设计的方法在低功率微处理器中具有良好的性能。     

面向384×288面阵型红外读出电路的低功耗设计

介绍了一种面向384×288 CMOS面阵性红外读出电路的低功耗设计.针对探测器的特点(输出阻抗约100kΩ,积分电流约100nA),新提出并实现了一种四像素共用BDI的QSBDI(Quad-share BDI)像素结构.在QSBDI结构中,4个相邻的像素共用一个反馈放大器,从而实现了高注入效率、稳定的偏置、较好的FPN特性和低功耗.另外该384×288读出电路还支持积分然后读出、积分同时读出功能,还有两个可选择的增益以及4种窗口读出模式.128×128的测试读出电路已完成设计、加工和测试.电路使用CSMC0.5μm DPTM工艺流片,测试结果表明在每个子阵列输出的峰峰差异仅为10mV.在4MHz的工作频率下,像素级引入的功耗仅为1mW,芯片的整体功耗也只有37mW,实现了低功耗设计.