带乘性噪声广义系统状态最优估计算法

针对带乘性噪声广义系统,提出1种在线性最小方差意义下的状态最优估计算法.首先,采用标准分解将系统变换为2个子系统;其次,通过估计子系统的状态,获得原系统的状态最优滤波.同时,算法还给出了动态噪声与量测噪声的估计.仿真结果表明了该算法的有效性.     

GNSS变形监测网短基线时间序列噪声特性分析

利用时间跨度为5 a的GNSS短基线时间序列对噪声特性进行分析,发现长周期噪声分量(随机游走噪声)。选取最优噪声模型,评估不同噪声模型对测站周期振幅和线性速度估值的影响。结果表明,短基线时间序列中有色噪声应顾及闪烁噪声和随机游走噪声,对于表现出随机游走噪声的分量,可能与测站的真实运动有关;假设只有白噪声时求得的速度估值与最优噪声模型下求得的速度估值存在0.4～0.6 mm/a的偏差,对周期振幅的影响可以忽略。     

Experimental Study of a Command Governor Adaptive Depth Controller for an Unmanned Underwater Vehicle

Unmanned Underwater Vehicles (UUVs) are increasingly being used in advanced applications that require them to operate in tandem with human divers and around underwater infrastructure and other vehicles. These applications require precise control of the UUVs which is challenging due to the non-linear and time varying nature of the hydrodynamic forces, presence of external disturbances, uncertainties and unexpected changes that can occur within the UUV’s operating environment. Adaptive control has been identified as a promising solution to achieve desired control within such dynamic environments. Nevertheless, adaptive control in its basic form, such as Model Reference Adaptive Control (MRAC) has a trade-off between the adaptation rate and transient performance. Even though, higher adaptation rates produce better performance they can lead to instabilities and actuator fatigue due to high frequency oscillations in the control signal. Command Governor Adaptive Control (CGAC) is a possible solution to achieve better transient performance at low adaptation rates. In this study CGAC has been experimentally validated for depth control of a UUV, which is a unique challenge due to the unavailability of full state measurement and a greater thrust requirement. These in turn leads to additional noise from state estimation, time-delays from input noise filters, higher energy expenditure and susceptibility to saturation. Experimental results show that CGAC is more robust against noise and time-delays and has lower energy expenditure and thruster saturation. In addition, CGAC offers better tracking, disturbance rejection and tolerance to partial thruster failure compared to the MRAC.     

BDS3新试验卫星测距信号质量分析

中国的北斗卫星导航系统按照“三步走”的发展战略稳步推进,目前正处于第二代区域卫星导航系统向第三代全球卫星导航系统发展的关键时期。在郑州设置实验测站,实地采集BDS3新试验卫星的数据,分别从卫星可见数、信号频点、载噪比、伪距观测噪声值、多路径效应等方面分析BDS3试验卫星测距信号的质量。结果表明:对于相同频点,不同卫星的载噪比、伪距噪声、多路径效应变化略有不同,一般而言,倾斜同步轨道卫星(IGSO)的性能优于中轨道卫星(MEO)的性能;相同轨道类型的卫星,载噪比、伪距噪声、多路径效应水平相似,并且载噪比、伪距噪声、多路径效应在各个频点的相对大小关系基本一致。     

基于分数阶和二阶总广义变分的乘性去噪模型

针对总变分(TV)模型在去噪时会产生阶梯效应、纹理细节信息丢失的问题,提出一种新的乘性噪声去除模型。该模型采用分数阶变分(FV)和二阶总广义变分(TGV)的正则项。FV的正则项在去噪时可保留图像的纹理信息,TGV的正则项在去噪时可改善阶梯效应。为有效求解该模型,先采用分裂法和交替方向法将原问题转化为两个相关的子问题,再利用原始对偶和梯度下降算法分别对子问题进行求解。对仿真图像进行实验的结果表明,新模型不仅可以提高图像的信噪比,而且可以更好地保留图像的边缘和纹理细节信息,改善阶梯效应。     

2～18 GHz超宽带低噪声放大器芯片研制

低噪声放大器在射电天文望远镜接收机中是一个重要的前端组件,其性能对接收机的灵敏度和噪声有至关重要的影响。采用OMMIC公司70 nm GaAs mHEMT工艺研究和设计了一款工作频率为2~18 GHz的超宽带单片微波集成低噪声放大器芯片,芯片面积为2 mm×1 mm。放大器电路采用三级级联放大、双电源供电拓扑结构,常温在片测试结果显示,全频带增益大于28 dB,噪声温度平均值为93 K,直流功耗150 mW,无条件稳定。该放大器芯片覆盖了射电天文S,C,X,Ku 4个传统观测波段,适用于厘米波段超宽带接收前端和毫米波段超宽带中频放大模块。     

顾及有色噪声的自适应粒子滤波UWB定位算法

传统卡尔曼滤波算法要求噪声模型符合高斯分布,在UWB室内定位中,由于载体本身的机制等干扰,观测噪声不仅仅是白噪声,也存在有色噪声的情况,而粒子滤波可以处理有色噪声的问题。本文通过增加似然分布自适应调整来改进粒子滤波用于目标跟踪的精度,同时研究在白噪声、有色噪声下似然分布自适应调整粒子滤波和拓展卡尔曼滤波在UWB中的优势与不同。试验结果表明：观测噪声为白噪声时,拓展卡尔曼滤波和粒子滤波均可以较好地实现对行人的定位跟踪;观测噪声为有色噪声时,自适应粒子滤波定位效果优于粒子滤波、拓展卡尔曼滤波。     

河北省数字地震台网子台地动噪声分析

通过对河北省数字遥测地震台网子台地动噪声分析,各个子台的台址环境和观测仪器的性能基本优良,能够适应宽频带地震观测要求。由于子台受当地经济发展、城市规模扩大以及交通建设等影响,部分台址观测条件受到影响。可以有针对性地对部分台站进行环境改造,为地震监测预报创造更好条件。     

Quality influencing factors of dispersion curves from short period dense arrays based on a convolutional neural network across the north section of the Xiaojiang fault area

The number of dispersion curves increases significantly when the scale of a short-period dense array increases. Owing to a substantial increase in data volume, it is important to quickly evaluate dispersion curve quality as well as select the available dispersion curve. Accordingly, this study quantitatively evaluated dispersion curve quality by training a convolutional neural network model for ambient noise tomography using a short-period dense array. The model can select high-quality dispersio...     

GPS变形监测动态数据处理中卡尔曼滤波的应用

介绍了卡尔曼滤波的基本原理,针对常规GPS变形监测数据处理中存在着不连续、非实时的缺点,结合卡尔曼滤波的特点,运用三峡实测数据对GPS变形监测动态数据处理中卡尔曼滤波的应用进行研究。并采用各点点位位移速度图对所建立的函数模型进行验证,同时对状态方程的建立及初始值的选取进行分析总结。