ID	原文	译文
56588	卡尔曼滤波器作为主体融合框架,融合局部传感器(IMU)和全局传感器(经优化后的视觉、GPS、磁力计和气压计)信息得到全局位姿估计.	The Kalman filter is considered the main structure of the fusion framework, which fuses a local sensor(IMU) and global sensors (aligned global visual inertial odometry, GPS, magnetometer, and barometer sensors)to obtain global state estimation in real time.
56589	由于卡尔曼滤波算法计算量较小,可以保证融合估计的实时性.	Global optimization estimates the transformation between localbase frame of the visual inertial odometry and global base frame to obtain an accurate global visual estimation.
56590	全局优化则负责将有漂移的视觉惯性里程计信息与全局传感器(GPS,磁力计和气压计)融合对齐后,得到高精度的全局视觉估计.但优化输出会出现不连续且视觉处理存在延迟的问题.因此,将优化后的里程计再输入到卡尔曼滤波器中,从而得到高精度、实时无漂移的状态估计.	However, given discontinuity of optimization and odometry delay, the aligned visual odometry is then input intothe Kalman filter to achieve accurate and drift-free state estimation in real time.
56591	最后结合具体无人机平台,进行了实际的飞行测试与定位实验,实验结果表明了本文方法的有效性和鲁棒性.	Finally, flight and localizationtests on a practical UAV were conducted. The experimental results demonstrate the effectiveness and robustnessof the proposed multi-sensor fusion method.
56592	为应对网络空间中的未知安全漏洞, 拟态防御系统作为一种动态异构冗余的新型防御架构破茧而出.	Cyber mimic defenses have recently emerged as a dynamic heterogeneity redundancy architecture,which adjust the asymmetry between defenders and attackers by reconfiguring the system according to the networkscenario.
56593	拟态系统根据网络环境自发进行重配置, 扭转了传统静态网络攻防不对等的局面.然而目前仍缺乏有说服力的能够定量评估并比较不同的安全防御系统有效性的实用方案.	Some studies have investigated the effectiveness of security models, however, there is still a lack ofconvincing and practical methods to assess CMD networks quantitatively.
56594	本文深入研究拟态架构, 提出了一种二维分析模型, 该模型将系统配置细节计算为量化结果, 以比较不同动态网络的可靠性, 且该模型在不同网络配置间可保持良好的可扩展性.	Thus, in this paper, we propose atwo-dimension model that calculates those details as a digital result to compare different CMD networks. Inaddition, the proposed method demonstrates good scalability in different networks.
56595	具体来说, 在分析的第 1 维度即单节点攻击分析时, 我们详细介绍了系统配置, 使用广义随机 Petri 网模型对攻击者和防御者的行为分别进行描述建模, 刻画其对系统状态的影响.	Specifically, in the firstdimension, i. e. , attacking a single node, we elaborate on system configurations and employ the GeneralizedStochastic Petri net model to capture the effectiveness of different behaviors from gamers.
56596	结合泊松过程、常见漏洞和暴露以及常见漏洞评分系统, 我们对其影响设计函数进行赋值、量化计算.	To quantify the impactsof those behaviors, we parameterized them using a Poisson process, common vulnerabilities and exposures, andthe common vulnerability scoring system.
56597	在分析的第 2 个维度即链路攻击中, 我们采用马尔可夫 (Markov)链, 并用鞅理论进行计算, 量化表达了攻击难度即攻击得手时长和网络配置之间的关系.	In the second dimension, we adopt Markov chains and the Martingaletheory to analyze the attack process along the attack chain.