检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

847 篇 会议
17 篇 期刊文献
1 篇 学位论文

馆藏范围

865 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

629 篇 工学
- 348 篇 电气工程
- 193 篇 计算机科学与技术...
- 185 篇 信息与通信工程
- 121 篇 软件工程
- 88 篇 航空宇航科学与技...
- 87 篇 测绘科学与技术
- 38 篇 电子科学与技术（可...
- 36 篇 仪器科学与技术
- 31 篇 控制科学与工程
- 30 篇 光学工程
- 11 篇 机械工程
- 9 篇 建筑学
- 9 篇 土木工程
- 8 篇 船舶与海洋工程
- 7 篇 生物医学工程（可授...
- 7 篇 安全科学与工程
- 6 篇 水利工程
- 6 篇 化学工程与技术
- 6 篇 生物工程
408 篇 理学
- 327 篇 物理学
- 58 篇 数学
- 19 篇 统计学（可授理学、...
- 18 篇 系统科学
- 11 篇 化学
- 11 篇 海洋科学
- 11 篇 生物学
- 6 篇 地球物理学
115 篇 医学
- 113 篇 临床医学
19 篇 管理学
- 10 篇 图书情报与档案管...
- 9 篇 管理科学与工程(可...
7 篇 军事学
4 篇 法学
3 篇 经济学
3 篇 文学
1 篇 教育学

主题

99 篇 signal processin...
74 篇 sensors
72 篇 target detection
67 篇 target tracking
62 篇 radar
60 篇 detection and tr...
55 篇 signal to noise ...
45 篇 object detection
44 篇 filtering (signa...
41 篇 signal processin...
40 篇 data association
36 篇 data fusion
33 篇 error analysis
31 篇 electronic filte...
30 篇 signal detection
30 篇 feature extracti...
30 篇 radar signal pro...
28 篇 data processing
26 篇 clutter
25 篇 data modeling

机构

19 篇 univ connecticut...
10 篇 cyberrnd inc cul...
7 篇 univ calif san d...
6 篇 numerica corp lo...
6 篇 univ connecticut...
5 篇 key laboratory o...
5 篇 numerica corp lo...
4 篇 qinetiq ltd malv...
4 篇 nanjing research...
4 篇 univ connecticut...
4 篇 raytheon co walt...
4 篇 national key lab...
4 篇 national laborat...
3 篇 beijing key labo...
3 篇 royal institute ...
3 篇 mcmaster univ de...
3 篇 numerica corp ft...
3 篇 sri int menlo pk...
3 篇 radar research l...
3 篇 mcmaster univ ec...

作者

19 篇 kirubarajan t
18 篇 bar-shalom y
17 篇 kirubarajan t.
17 篇 bar-shalom yaako...
14 篇 willett peter
12 篇 blair wd
10 篇 drummond oliver ...
9 篇 tharmarasa r.
8 篇 sinha a
7 篇 drummond oe
7 篇 willett p
6 篇 huang jim
6 篇 daum fred
5 篇 maskell s
5 篇 romeo kevin
5 篇 barshalom y
5 篇 danford scott
5 篇 xing mengdao
4 篇 pattipati kr
4 篇 paffenroth randy

语言

856 篇 英文
4 篇 其他
3 篇 中文
2 篇 土耳其文

检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2000"

共 865 条记录，以下是71-80 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Sea Surface small Target Tracking Method with Integrated Dynamic Wave Prediction Information

Sea Surface Small Target Tracking Method with Integrated Dyn...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Zixuan Li Biao Jin Kangsheng Sun Chao Liu Ocean College Jiangsu University of Science and Technology Zhenjiang China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Tracking small targets on the sea surface has always been a challenging issue in the field of maritime target monitoring. Traditional methods typically rely on specific dynamic equations to establish the motion state model of the target (such as CV, CA, and CT models or their combinations), which struggle to accurately represent the motion states of small targets under complex sea conditions. We propose a method that incorporates deep learning to predict the dynamic fluctuations of sea waves, integrating real-time wave state information into the target state model. This method, which fuses sea wave dynamic prediction information, aims to improve the tracking of small sea surface targets. Firstly, we simulate various sea conditions based on the Elfouhaily wave spectrum to establish a database of small target motion trajectories on the sea surface. Then, we employ an LSTM network with a dual-stage attention mechanism to predict wave heights, which are subsequently fed into the state transition model. We utilize the Extended Kalman Filter for tracking. Simulation results demonstrate that with the assistance of sea wave dynamic prediction information, the proposed method enhances target tracking accuracy by approximately 14% compared to traditional methods.

关键词： Sea surface Target tracking Surface waves Dynamics Predictive models Mathematical models Trajectory Kalman filters Vehicle dynamics Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Examination of Micro-Doppler Signatures of Drone and Seagulls with X-Band Noise Radar

Examination of Micro-Doppler Signatures of Drone and Seagull...

引用

IEEE signal processing and Communications Applications (SIU)

作者： Kartal Kaan GÜMen Selçuk Paker Kubilay Savci Uydu Haberleşmesi ve Uzaktan Algılama İstanbul Teknik Üniversitesi İstanbul Türkiye Elektronik ve Haberleşme Mühendisliği İstanbul Teknik Üniversitesi İstanbul Türkiye Elektrik ve Elektronik Mühendisliği Koç Üniversitesi İstanbul Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

In this study, data obtained from near-range radar responses collected by an X-band noise radar targeting small aerial objects such as drones and seagulls have been analyzed for the purpose of target discrimination. The research aims to identify distinctive features in terms of range, speed, and micro-Doppler signatures of small air targets using a noise radar operating at the same frequency as maritime ship radars. This approach has not only facilitated the detection of small air targets with low Radar Cross Section (RCS) but also contributed additional information for classifying these targets. Considering that the noise radar used during the measurements possesses characteristics typical of a marine radar, this work has effectively demonstrated the extraction of micro-Doppler signatures of drones and seagulls performing various maneuvers in a maritime environment.

关键词： Radar cross-sections Noise Radar detection Radar Radar signal processing Doppler radar Noise measurement

来源：评论

学校读者我要写书评

暂无评论

data-dependent Channel Selection Method for STAP based on MVDR Criterion

Data-dependent Channel Selection Method for STAP based on MV...

引用

IET International Radar conference 2023, IRC 2023

作者： Li, Yu Chen, Jinming Cheng, ZiYang Wang, Weiwei Zhang, Jun Wu, Tao Duan, Chongdi Xi'an Institute of Space Radio Technology No.504 East Changan Street Changan district Xi'an China University of Electronic Science and Technology of China No. 2006 Xiyuan Street West Gaoxin district Chengdu China

ISBN: (纸本)9781839539954

Space-time adaptive processing (STAP) combines the returned signals from all elements of an antenna array and all coherent pulse trains during a CPI period to provide clutter suppression and target detection ability, which is a promising technique for acquiring small, slow, and moving targets. In this work, we proceed to the data-dependent channel selection method for Post-Doppler beam- space STAP to improve clutter suppression performance in sample starved environments, in which no additional a prior information is used in our framework. The main innovation of this manuscript lies in the characteristic that the selected channels in the fully-dimension weight vector, which is inversely transformed from the RD weight vector, is sparse relative to the whole beam-Doppler channels. Compared with several existing methods, the proposed method significantly enhances the STAP performance in sample starved environments. © The Institution of Engineering & Technology 2023.

关键词： Space time adaptive processing

来源：评论

学校读者我要写书评

暂无评论

HRTD: A high-precision rotating target detector for SAR scenes

HRTD: A high-precision rotating target detector for SAR scen...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Zheng Zhou Yijun Li Zongyong Cui Yiming Pi Zongjie Cao University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In the past, synthetic aperture radar (SAR) target detection research has mainly focused on the representation of bounding boxes. However, the distant contextual prior knowledge in SAR images has not been fully utilized, leading to challenges in detecting small targets and densely arranged targets with multi-scale characteristics. Therefore, this paper proposes a high-precision rotating target detector (HRTD) for SAR scenarios to address the aforementioned issues. More precisely, we introduce a multi-scale rotation-equivariant network (MRNet) and align rotation-invariant regions of interest to enhance target orientation prediction capability. The multi-scale dynamic global attention (MDGA) in MRNet can dynamically adjust the contextual multi-scale spatial receptive field in real-time, facilitating the comprehensive extraction of distant contextual features. This method achieves significantly better detection performance on the SSDD+ and SRSDD-v1.0 datasets compared to other algorithms.

关键词： Heuristic algorithms Detectors Object detection Feature extraction Prediction algorithms data processing Real-time systems Radar polarimetry data mining Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

A Low-Altitude small Target Radar Recognition Algorithm Based on Micro-Doppler Features and Vision Transformer Network

A Low-Altitude Small Target Radar Recognition Algorithm Base...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Guangmao Chen Haibo Liu Radar Technology Research Institute School of Information and Electronics Beijing Institute of Technology Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan 250300 China Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In low-altitude airspace surveillance scenarios, accurately distinguishing between birds and unmanned aerial vehicles (UAVs) is of vital importance. However, the high similarity in flight altitude and speed between birds and UAVs makes it extremely difficult to distinguish between these two types of targets. To enhance radar recognition performance for both UAVs and birds, this paper proposes a low-altitude target recognition algorithm that combines micro-Doppler features with a Vision Transformer network (ViT) under a staring radar system. Verified with real-measured data, the recognition accuracy for three types of UAVs and birds reaches 94%.

关键词： Computer vision Accuracy Target recognition Surveillance Radar Birds Transformers data processing Robustness Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

FANM: Fuzzy-Aware Nested Mamba for Infrared Dense small Target Detection

FANM: Fuzzy-Aware Nested Mamba for Infrared Dense Small Targ...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Yi Sui Xiyang Zhi Yuanxin Huang Xiaoyang Liang Zheng Lu Wei Zhang Research Center for Space Optical Engineering Harbin Institute of Technology Harbin China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The task of infrared dense small target detection aims to accurately locate densely distributed thermal radiation targets in complex scenes. However, in complex scenes, dense small targets often suffer from occlusion, shadows, and blurriness, leading to unclear detection bounding boxes and inaccurate localization. To address the aforementioned issues, this paper introduces an innovative approach for infrared dense small target detection, termed the Fuzzy-Aware Nested Mamba (FANM) network. Specifically, the network takes a single-frame infrared image as its input and leverages shallow, middle, and deep Mamba networks to fully exploit and integrate local and global multi-scale features. The extracted features are subsequently passed to a feature pyramid network (FPN) to balance the spatial resolution and semantic information of each feature map layer, ensuring that feature maps of different scales can be effectively utilized. Then, the output features at each level are fed into the detection head, which consists of two branches: one for regressing the positions of arbitrarily distributed bounding boxes, and the other for predicting the quality of the bounding boxes. The proposed fuzzy perceptual loss function is used to optimize these branches, ultimately outputting images with accurately detected target bounding boxes. Experiments were performed on the DMIST dataset, which includes images with varying numbers of targets, and the results validate the effectiveness of our method.

关键词： Location awareness Head Accuracy Uncertainty Semantics Object detection Feature extraction data mining Spatial resolution Optimization

来源：评论

学校读者我要写书评

暂无评论

Target Location in Distributed MIMO radar based on Coherent processing

Target Location in Distributed MIMO radar based on Coherent ...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Fa Wei Shi Yan Shengqi Zhu Lan Lan Ximin Li Jiawei Qi Runlong Ma National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Beijing Institute of Remote Sensing Device Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In this paper, the problem of target location is investigated in the distributed multiple-input multiple-output (MIMO) radar based on coherent processing. At the modelling stage, the distributed MIMO radar is divided into three separated subarrays, where both transmit and receive functions are used in subarrays 1 and 3, while only receive function is adopted in subarray 2. Furthermore, a small frequency increment is introduced among different antenna elements in the subarray 1, in the meantime, a phase modulating operation is performed for various antenna elements in the subarray 3. In this respect, the target location performance can be improved significantly by means of the transmit modulation in subarrays 1 and 3. Under the circumstances, the model of target location is established, and a two-step estimation technology is shown, where a small location sector with respect to targets are firstly obtained, and the accurate location are further estimated. Specifically, in order to reduce the computational cost required by the multi-dimensional search procedures, an alternating procedure is developed by a sequence of 1-D searches obtained alternating between the optimization over each variable keeping the other fixed. Numerical results corroborate the effectiveness of the developed methods for the target location with distributed MIMO radar based on coherent processing.

关键词： Frequency modulation Phase modulation MIMO radar Estimation Search problems data processing Encoding Optimization Antennas MIMO communication

来源：评论

学校读者我要写书评

暂无评论

Open Set HRRP Recognition Using Adaptive Learning with Enclosed Decision Boundaries

Open Set HRRP Recognition Using Adaptive Learning with Enclo...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Binhua Yu Ping-An Liu Yichen Liu Hongyu Wang Liang Zhang Yanhua Wang Kun Liu Radar Technology Research Institute Beijing Institute of Technology Beijing China Xi’an Modern Control Technology Research Institute Xi’an China Zhengzhou Academy of Intelligent Technology Beijing Institute of Technology Zhengzhou China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

High resolution range profiles (HRRP), which contain fine geometric structure information of targets, plays animportant role in the field of Radar automatic target recognition (RATR). In the actual application of RATR, radar may often capture targets that are non-cooperative, making it difficult to establish a comprehensive database, and traditional recognition algorithms are prone to misjudgment when facing unknown targets. Therefore, Open set recognition (OSR) is proposed to simultaneously recognize in-database and out-of-database targets. Considering the pose sensitivity of HRRP, minor changes in the target’s pose can cause significant changes in the HRRP images, leading to a potentially dispersed distribution of samples from the same category in the feature space, which makes it difficult for traditional fixed decision boundaries in OSR to adapt. To address this, this paper proposes an HRRP open set recognition method capable of adaptively learning closed decision boundaries. Based on Hierarchical dirichlet processes (HDP), the method achieves adaptive clustering of subclasses under different categories according to the data distribution characteristics of each category, determining multiple small decision boundaries within each category, and allowing the decision boundaries to dynamically adjust according to the sample features. Finally, experiments with real HRRP data have verified the effectiveness of the proposed method.

关键词： Training Sensitivity Image resolution Image recognition Target recognition databases Imaging Radar applications signal resolution Dispersion

来源：评论

学校读者我要写书评

暂无评论

Multi-view Bistatic SAR Automatic Recognition Study based on Ground small Target SAR dataset

Multi-view Bistatic SAR Automatic Recognition Study based on...

引用

signal, Information and data processing (ICSIDP), IEEE International conference on

作者： Jiming Lv Daiyin Zhu College of Electronics and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Faculty of Engineering Niigata University Niigata Japan Shenzhen Research Institute Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

MiniSAR systems possess unique advantages in ground target detection compared to traditional spaceborne and airborne SAR systems, mainly in terms of lower cost, real-time performance, and portability. Although numerous studies have focused on target recognition based on SAR systems with unmanned aerial vehicle, most are limited to monostatic SAR systems. Bistatic SAR systems offer stronger stealth capabilities compared to monostatic systems, as they can receive electromagnetic reflections from any angle. However, due to the lower intensity of received electromagnetic signals in bistatic systems, targets in SAR images tend to experience deformation and attenuation. In this study, based on independently developed monostatic and bistatic SAR systems, we study the integration of multi-view and large-scale deep learning models to aiming to address the issue of hard to recognized small targets. Additionally, the paper validates our proposed method on the publicly available MSTAR dataset and the self-developed FAST-Vehicle dataset. Experimental results demonstrate that the proposed multi-view target recognition method effectively identifies SAR bistatic deformed targets.

关键词： Training Image recognition Accuracy Target recognition Imaging Object detection Transformers Radar polarimetry Real-time systems Electromagnetics

来源：评论

学校读者我要写书评

暂无评论

AugTarget data Augmentation for Infrared small Target Detection

AugTarget Data Augmentation for Infrared Small Target Detect...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Shengjia Chen Jiewen Zhu Luping Ji Hongjun Pan Yuhao Xu School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Sichuan University Chengdu China

Sample shortage has always been a frequently-faced problem for the machine-learning models in infrared small target detection. As one of main limitations, it is hampering the further promotion of target detection performance. In this paper, we propose a simple and effective data augmentation scheme, AugTarget, to address this shortage issue of small target samples. Our scheme mainly consists of two crucial algorithms: target augmentation and batch augmentation. The former is designed to generate sufficient targets, by random target representation. The latter is devised to diversify training samples. Moreover, the initially-generated image samples of small targets are further enriched by randomly aggregating the feature representation of different images. The experiments on public datasets demonstrate that our AugTarget could bring an obvious improvement to mean intersection over union (mIoU). Cooperated by the augmentation of our AugTarget, the state-of-the-art (SOTA) method, AGPC could even achieve a distinct performance promotion by 3.03%, 2.17% and 2.63% on MDFA, SIRST-Aug and Merged datasets, respectively. In addition, the experimental results on three baseline models also show the universality & adaptivity of AugTarget to different dataset augmentation. Our source codes are available at https://***/UESTC-nnLab/AugTarget.

关键词： Training Adaptation models Source coding signal processing algorithms Object detection Machine learning signal processing

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共87页 << < 4 5 6 7 8 9 10 11 12 13 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：