基于磁强计和光纤陀螺的小卫星姿态确定非线性滤波算法

提出了一种小卫星姿态确定的非线性滤波算法,该算法利用三轴磁强计和光纤陀螺作为姿态敏感器。在非线性滤波器的设计中,从两个方面对平方根sigma点卡尔曼滤波方法进行改进。第一,把姿态四元数的矢量部分、光纤陀螺的漂移和噪声组合,得到滤波器的增广状态向量;第二,分别建立向量旋转模型、最优化模型和误差四元数乘法模型来确保非线性滤波过程中四元数的归一化约束。仿真分析结果表明,本文提出的非线性滤波算法能够有效地提高小卫星的定姿性能,与扩展卡尔曼滤波相比,具有较高的精度、稳定性和较快的收敛速度;与无迹卡尔曼滤波相比,收敛性相当,但是精度略优,稳定性和计算效率较高。     

距离伪量测的空基平台单站无源定位算法

针对空中观测单站平台对海面、地面目标的测向定位问题,提出一种基于距离伪量测的最小二乘-不敏卡尔曼滤波(LSE-UKF)两阶段滤波算法。首先利用单次的测角信息以及目标离地高度的约束条件计算出目标的距离,采用最小二乘法对距离量进行滤波,得到较为准确的距离量。进一步将滤波所得距离量视为伪量测信息,结合观测所得的角度信息进行不敏卡尔曼滤波。仿真实验表明该算法提高了定位精度并且具有较快收敛速度。     

不同转位方案下双轴旋转惯导系统精对准分析

针对双轴旋转惯导系统转位方案的设计和选择问题,提出了3种合理的转位方案:16次序、24次序和32次序,建立了旋转惯导系统的误差方程和卡尔曼滤波模型.观测量取速度误差和位置误差时,分别对3种转位方案下精对准过程进行了分析仿真.结果表明,24次序转位方案精对准过程所需时间最短,精度最高,其次是32次序,16次序转位方案精对准过程所需时间最长,精度最低.     

卫星导航弱信号的变维卡尔曼滤波跟踪算法

复杂环境下的多普勒频移变化及信号功率衰减均会造成载波跟踪偏差较大甚至失锁,针对标准卡尔曼滤波算法跟踪机动目标时不能同时满足高动态及高灵敏度要求的问题,提出一种基于变维卡尔曼滤波的载波跟踪算法。引入机动和非机动两种载波跟踪模型,通过机动检测因子监视载波动态变化,实时高效地切换载波跟踪模型,从而实现对载波机动和非机动状态的自适应跟踪,抑制机动改变引起的较大误差突跳。理论分析和仿真结果表明,该算法在低至30d BHz弱信号环境下,相比基于标准卡尔曼滤波的跟踪算法,其在目标动态突变时相位跟踪误差减小约37.5%,频率跟踪误差减小约77%。     

SPEED BUMP ON THE ROAD TO GLOBAL ZERO

The prospect of the United States continuing to reduce the size of its nuclear arsenal to “very low numbers” has raised questions in Japan and South Korea, where US extended deterrence guarantees are premised on the “nuclear umbrella.” In both countries, however, concerns focus less on numerical arsenal size than on the sufficiency of specific nuclear and non-nuclear capabilities to meet evolving threats and on the degree of broader US commitment to these alliances. This article assesses developments in US-Japan and US-South Korea relationships in response to the Obama administration's nuclear disarmament policies, focusing on how the evolutionary course of those relationships may in turn condition prospects for sustaining this US nuclear policy direction. The analysis finds that the challenges of deterrence credibility and allied reassurance are difficult and long-term, but also that US nuclear arsenal size is secondary to broader political, strategic, and military factors in meeting these challenges. The evaluation concludes that strong alliance relationships and strategic stability in East Asia can be maintained while the size of the US nuclear arsenal continues to decline, but also that deterioration of these relationships could imperil core US nuclear policy and nonproliferation objectives.     

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。     

Visual-simulation region proposal and generative adversarial network based ground military target recognition

Ground military target recognition plays a crucial role in unmanned equipment and grasping the battlefield dynamics for military applications, but is disturbed by low-resolution and noisy-representation. In this paper, a recognition method, involving a novel visual attention mechanism-based Gabor region proposal sub-network (Gabor RPN) and improved refinement generative adversarial sub-network (GAN), is proposed. Novel central–peripheral rivalry 3D color Gabor filters are proposed to simulate retinal structures and taken as feature extraction convolutional kernels in low-level layer to improve the recognition accuracy and framework training efficiency in Gabor RPN. Improved refinement GAN is used to solve the problem of blurry target classification, involving a generator to directly generate large high-resolution images from small blurry ones and a discriminator to distinguish not only real images vs. fake images but also the class of targets. A special recognition dataset for ground military target, named Ground Military Target Dataset (GMTD), is constructed. Experiments performed on the GMTD dataset effectively demonstrate that our method can achieve better energy-saving and recognition results when low-resolution and noisy-representation targets are involved, thus ensuring this algorithm a good engineering application prospect.     

基于Kalman滤波器的放大转发双向中继联合信道估计方法

针对遵从放大转发协议的双向中继网络的联合信道估计问题,提出了一种基于Kalman滤波器的新方法。首先根据联合信道构成特点将其划分为自干扰部分及传输部分,通过AR模型对这两部分自相关函数进行近似化处理,建立了联合信道时变过程的状态方程,结合接收的训练序列信号,给出了具有Kalman滤波器形式的估计方法。随后在证明了该方法的一致收敛性质的同时,列出了误差性能限所满足的Riccati方程表达式。仿真结果表明,新估计方法相比于最大似然方法在均方误差方面具有明显的性能优势。     

结合非负张量表示与扩展隐Dirichlet分配模型的图像标注

由于"语义鸿沟"的存在,自动图像标注是一项极具挑战性的工作。考虑到图像低层视觉特征与高层语义概念的差异,分别从图像表示与语义建模两个方面来实现自动图像标注。在图像表示方面,提出了一种正则化约束下的非负张量表示方法,用以提取符合人眼视觉直观理解的图像高阶结构特征。在语义建模方面,提出了一种三层贝叶斯模型——扩展隐Dirichlet分配。该模型利用隐变量来实现图像与标注词的关联,并通过一种基于变分推理的期望最大值方法来估计参数。实验结果表明,ELDA模型在大规模数据库NUS-WIDE上的标注结果相较于现有方法有了显著的提高。     

振动信号变换器的设计与实现

多传感器采编器能够实现复杂环境下对飞行体在发射过程中振动加速度、冲击加速度、压力、温度等动态参数的实时测量和记录。传感变换器电路的性能直接影响采集系统的采样精度。为了实现准确测量,对广泛应用于工程实践中的高阶集成开关电容滤波器产生的混叠效应的抑制方法进行分析及实验。实现了一种可程控放大、具有稳定通带截止频率的振动信号变换器设计。实验结果表明,该变换器电路具有体积小、集成度高、滤波衰减陡度大,频率测试精度高等特点。