本文研究的雷达目标识别器结合了毫米波(MMW)和LFMCW雷达的优点，课题主要完成了对毫米波lfmcw雷达目标识别器的硬件设计和调试。
This thesis talk about millimeter wave (MMW) and LFMCW, its main mission is design and debug hardware of the radar target processor.
这两个协议都使用端点标识符来识别服务器端中间件中的目标对象，且它们都使用方法标识符来确定待调用方法的签名。
Both protocols use endpoint identifiers to identify a target object within the server-side middleware and they both use method identifiers to determine the signature of the method to be invocated.
该公司的3D算法能够从多个传感器融合数据，实现高清快速3D制图和可靠的目标识别。
Technest\'s 3D sensing algorithm fuses data from multiple sensors to achieve high-resolution rapid 3D mapping and reliable object recognition.
改进目标识别的新传感器以及其他目标识别和辨别特征。
New sensors for improved target identification; and other target recognition and identification features.
在目标识别中，单个传感器的目标识别性能很有限。
The performance of target recognition is usually limited when using single sensor.
将该方法用于一个目标识别任务的仿真实验，结果表明应用该方法能确定地识别出目标，是一种有效可行的多传感器数据融合方法。
By applying the method to the target identification, the simulation experiment shows that it can identify the target accurately and is an effective and feasible multi-sensor data fusion method.
在对空袭目标信息进行综合利用的基础上，建立了基于黑板模型的多传感器空袭目标识别融合专家系统模型，模拟专家识别思维。
An expert system of air attack target recognition model based on blackboard model is built after the target information is synthesized, it can simulate the recognition thought of the domain experts.
文章对被动声纳目标识别的特征提取、特征选择和分类器设计方面进行了回顾。
The techniques of feature extraction, feature selection and design of classifier for passive sonar target recognition are reviewed.
该文详细讨论了基于HRRP的雷达自动目标识别的关键技术及研究现状，包括雷达hrrp的特性、预处理方法、特征提取方法及分类器设计方法等。
In this paper, we review the present research status and some key techniques in this field, including the property of HRRP, preprocessing methods, feature extraction and classifier design.
目标识别技术属于模式识别理论的研究范围，其关键在于特征提取和分类器的设计。
The target identification technology belongs to the research scope of the pattern recognition, its key lies in the characteristic withdraw and the sorter design.
在目标识别中，毫米波敏感器和红外敏感器有各自独特的优势。
For target recognition, millimeter wave sensor and infrared sensor have their own unique advantage.
目标噪声特征提取和目标分类器设计是被动声呐目标识别系统的关键技术。
Feature extraction of targets radiated noise and design of targets classifier are key technique of passive sonar target recognition system.
目标噪声特征提取和目标分类器设计是被动声纳目标识别系统的关键技术。
Feature extraction of targets radiated noise and design of targets classifier are key issues of passive sonar target recognition system.
从分析侦察手段所处的战场环境入手，将模糊集理论引入单传感器目标识别算法中，提出了基于模糊匹配的单传感器目标识别算法。
The uncertain and its reason of battlefield environment are analyzed. Then Fuzzy Set theory is introduced to the single target identification algorithm.
提出了一种用于目标识别的多传感器雅息融合算法—后验概率检测算法。
A multiple sensor information fusion algorithms-posterior probability detection algorithms is presented and applied to target identification.
光传感器目标识别则是在取得目标的反射特性和辐射特性（光谱）后提取其特征进行识别。
Optical sensor target recognition extracts the characteristic of target to perform target recognition after having acquired its reflection and radiation (spectra) characteristics.
基于假设检验的方法，研究了目标识别中的传感器管理方法。
Based on hypothesis testing, methods of multisensor management used in target identification are studied.
本文介绍了激光器目标识别系统的结构和操作规律。
The paper introduces the overall structure and operation principle of a laser target identification system.
本文针对目标识别问题，论述了多传感器目标属性融合技术。
Techniques in multisensor target identity fusion for target identification are described in this paper.
针对空战目标识别中机型识别这一问题，提出了基于多分类器融合的识别方法。
Aiming at aircraft type recognition in the field of automatic target recognition, a method based on combining classifiers is proposed.
为了提高多级武器系统的作战性能，研究复杂干扰环境下的多传感器目标识别问题具有极其重要的意义。
So it is significant for improving performance of multilevel weapon system to study multi-sensor target recognition in a complex interference environment.
针对激光雷达一维距离像的目标识别，提出了利用最小二乘估计器和线性滑动更新器构造滤波器的算法。
A new arithmetic approach to the target identification of lidar range image was introduced by using the least squares estimation and linear glide updater for the design of a filter.
将本文所改进的算法应用于毫米波探测器目标识别，实验结果证明了算法的优越性能。
The proposed algorithms are used for target recognition of MMW detector and the experimental results indicate their good performance.
为了验证特征的有效性，使用最近邻及概率神经网络分类器进行了目标识别，得到满意的识别率。
In order to validate character validity, use NearestNeighbor (NN) and probabilistic neural network (PNN) classification identify target, gain content identification probability.
改进的算法可有效地应用于采用两种探测器的目标识别：毫米波辐射计、红外搜索和跟踪探测器。
The developed algorithms are applied to a target identification problem with two sensors: millimeter wave radiometer, infrared searching and tracking.
基于因素空间理论，建立一种多传感器多目标识别方法。
A multisensor decision fusion method was created based on theory of factor Spaces.
节点定位问题是传感器网络进行目标识别、监控、跟踪等众多应用的前提，对其研究具有非常重要的意义。
Localization is the precondition of many applications of sensor networks, such as target identification surveillance and tracking. Therefore, it is important to make research on it.
考虑到单传感器的系统存在着局限性，提出了基于多传感器(雷达和红外)信号融合的目标识别和跟踪系统，以利用数据的互补和冗余。
This paper presents the approaches of multi sensor (radar and infrared sensor) data fusion for object recognition and tracking, which can make use of the complement and redundancy of data.
通过优化支持向量机算法，将它嵌入到激光成像雷达系统的数字信号处理器(DSP)芯片内，实现目标识别的功能，有很高的现实意义。
Through optimizing the algorithm of SVM, it is embedded into digital signal processing (DSP) of laser imaging radar, achieving the function of target recognition, which has high pract.
通过优化支持向量机算法，将它嵌入到激光成像雷达系统的数字信号处理器(DSP)芯片内，实现目标识别的功能，有很高的现实意义。
Through optimizing the algorithm of SVM, it is embedded into digital signal processing (DSP) of laser imaging radar, achieving the function of target recognition, which has high pract.
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