sensor n. 1.=sensory (名词). 2.【自动化】感受器;传感器;灵敏元件,控制仪板上显示温度、辐射量等变动的装置。
multiple adj. 1.多重的;复合的,复式的,多数的,多样的。 2.倍数的,倍。 3.【电学】并联的;多路的,复接的。 4.【植物;植物学】聚花的。 a man of multiple interests 兴趣广博的人。 n. 1.【数学】倍数。 2.【电学】并联;多路系统。 3.相联成组。 4.成批生产的艺术品〔画、雕塑、工艺品等〕。 common multiple 公倍数。 least common multiple 最小公倍数。
The vector spectrum descends from the combination of multiple sensor information fusion and the rotary theory of rotor and its dynamic characters . multiple sensor information fusion means the fusion process of dynamic signals with the same source 多传感器信息融合是指动态信号在一定准则下加以自动分析、综合以完成所需的决策和评估而进行的信息处理过程。
The paper also proves that it is possible for mobile robot execute tasks under the guidance of environment - embedded sensors , and the accuracy of execute depends on the accuracy of the object detection , which can be improved by using multiple sensors 移动机器人可以在嵌于外部环境中的传感器的引导下执行任务,并且任务完成的精度和决定定位精度的传感器的数目有直接的关系。
According to a localization method of indoor intelligent cleaner , which includes a 2d kinematic modeling , multiple sensor fusion , an interval analysis based adaptive mechanism for an extended kalman filter , and corresponding simulation 摘要针对室内全自主智能吸尘器,建立了二维运动学模型和以超声传感为主的多传感器融合,并采用融合区间分析算法的扩展卡尔曼滤波处理方法,作了对比仿真实验。
A robotic arm fitted with multiple sensors extends from a regular petrol pump , carefully opens the car ' s flap , unscrews the cap , picks up the fuel nozzle and directs it toward the tank opening , much as a human arm would , and as efficiently 装备有多感应器的机器人手臂会从一个普通的汽油油泵延伸,小心翼翼打开汽车油箱翻盖、旋开箱盖、拿起加油管,朝着油箱口,大部分和人工一样的动作,并且同样有效。
Image fusion can combine complementary and redundant information from multiple sensors to achieve improved accuracies and more comprehensive than could be achieved by the use of a single sensor alone , which benefits for the feature extraction and target recognition 图像融合能够综合同一场景的多传感器图像的互补信息和冗余信息,获得比任何单一传感器对场景更为全面和精确的图像表述,从而有利于人眼观察和后续处理。
Significant investments in dod applications , rapid evolution of microprocessors , advanced sensors , and new techniques have led to new capabilities to combine data from multiple sensors for improved inferences . recently however , interest in wavelets has grown at an explosive rate 另外,由于在军事应用领域强大的发展潜力,微机系统的快速更新换代,更先进的传感器的出现以及新的融合技术的发展,多传感器数据融合的性能不断获得新的提高
Because observing patterns to be recognized from multiple sensors can well and truly reflect the features of them , eliminate the uncertainty of the information . pattern recognition methods based on information fusion have already been one of the development trends of pattern recognition field 从多传感器视角观察待识别模式能够完整准确的反映模式特征,消除观察信息的不确定性,因此,基于信息融合的模式识别方法已成为模式识别的发展趋势之一。
First , a new method of feature level fusion pattern recognition is presented . feature fusion coefficients are defined to fuse the features extracted from different view of multiple sensors . by evaluating different feature fusion coefficients to different features , we can get the fusion feature of the pattern to be observed 首先,提出一种特征层融合模式识别的方法,定义“特征融合系数”对多传感器视角观察模式所得的不同特征进行融合,通过对不同特征赋以不同的特征融合系数,将多特征进行融合,得到待识别模式的融合特征,从而实现特征层融合。
Data fusion technique synthesizes data from multiple sensors and related information from associated databases , to achieve improved accuracies and more specific inferences than those could be achieved by the use of a single sensor alone . it is actually an important part of current c3i systems and its process model contains the signal detection , position , identity assessment in low level and the situation assessment and the threat assessment in high level . meanwhile , it is also the integration of many traditional disciplines and new areas of engineering 数据融合,由于其综合多信息源的数据,与从任何单个信息源所获得的数据相比,提供更加精确和更加确定的推理;它是现代c3i系统中的重要组成部分,其功能模型中包括低层的信号检测,位置估计和身份估计,以及高层的态势估计和威胁估计;同时,它也是许多传统学科和新兴的工程领域相结合而产生的一项新技术。
How to use dempster - shafer ( d - s ) method to solve multi - sensor data fusion problems is analyzed in this paper . based on basic probability assignment of target type decided by multiple sensors , new sensor data are added continually , and believe function and plausibility function are update ; finally the destination of decision of target type is arrived 应用证据理论( d - s方法) ,解在多传感器条件下的数据融合问题,具体方法是根据多个传感器对目标类型判断的基本概率分配函数,不断添加新的传感器数据,更新信任函数和似然函数,最终判断目标类型。