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浏览/检索结果: 共10条，第1-10条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Echoformer: Transformer Architecture Based on Radar Echo Characteristics for UAV Detection 期刊论文 IEEE SENSORS JOURNAL, 2023, 卷号: 23, 期号: 8, 页码: 8639-8653 作者:  Yang, Yipu;  Yang, Fan;  Sun, Liguo;  Xiang, Ti;  Lv, Pin 收藏  |  浏览/下载：1/0  |  提交时间：2023/11/17 Radar  Radar detection  Clutter  Sensors  Frequency modulation  Task analysis  Radar measurements  Doppler frequency shift  micro-Doppler signature (mDS)  radar echo processing  Transformer  unmanned aerial vehicle (UAV) detection   Biological Eagle-eye Inspired Target Detection for Unmanned Aerial Vehicles Equipped with a Manipulator 期刊论文 Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 741-752 作者:  Yi-Min Deng, Si-Yuan Wang 收藏  |  浏览/下载：2/0  |  提交时间：2023/09/25 Unmanned aerial vehicle (UAV), eagle eye, multi-camera sensor, target detection, saliency detection   Motor Anomaly Detection for Unmanned Aerial Vehicles Using Reinforcement Learning 期刊论文 IEEE INTERNET OF THINGS JOURNAL, 2018, 卷号: 5, 页码: 2315-2322 作者:  Lu, Huimin;  Li, Yujie;  Mu, Shenglin;  Wang, Dong;  Kim, Hyoungseop 收藏  |  浏览/下载：7/0  |  提交时间：2019/12/02 Anomaly detection  reinforcement learning  temperature sensor  unmanned aerial vehicle (UAV)   Multisensor Data-Fusion-Based Approach to Airspeed Measurement Fault Detection for Unmanned Aerial Vehicles 期刊论文 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2018, 卷号: 67, 期号: 2, 页码: 317-327 作者:  Guo, Dingfei;  Zhong, Maiying;  Zhou, Donghua 收藏  |  浏览/下载：5/0  |  提交时间：2019/12/11 Airspeed estimation  fault detection (FD)  kinematics model  pitot tube  unmanned aerial vehicle (UAV)   SIMULTANEOUS DISTURBANCE COMPENSATION AND H-I/H-infinity OPTIMIZATION IN FAULT DETECTION OF UAVs 期刊论文 INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2018, 卷号: 28, 期号: 2, 页码: 349-362 作者:  Liu, Hai;  Zhong, Maiying;  Yang, Rui 收藏  |  浏览/下载：9/0  |  提交时间：2019/12/11 fault detection(FD)  H-i/H-infinity optimization  disturbance  compensation  unmanned aerial vehicle (UAV)   Multisensor Data-Fusion-Based Approach to Airspeed Measurement Fault Detection for Unmanned Aerial Vehicles 期刊论文 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2018, 卷号: 67, 页码: 317-327 作者:  Guo, Dingfei;  Zhong, Maiying;  Zhou, Donghua 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30 Airspeed estimation  fault detection (FD)  kinematics model  pitot tube  unmanned aerial vehicle (UAV)   Sensor bias fault detection and isolation in a large multirotor aerial vehicle using active disturbance rejection control 会议论文 AIAA Information Systems-AIAA Infotech at Aerospace, 2018, 2018-01-08 作者:  Li, D.W.;  Liu, H.H.T. 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/30 Aircraft detection  Antennas  Aviation  Commercial vehicle operations  Commercial vehicles  Disturbance rejection  Flight control systems  Information systems  Information use  Time varying systems  Unmanned aerial vehicles (UAV)  Active disturbance rejection controls  Commercial operation  Fault detection and isolation  Fault detection filter (FDF)  Luenberger observers  Nonlinear simulations  Robust fault detection  Sensor measurements  Fault detection   SIMULTANEOUS DISTURBANCE COMPENSATION AND H-I/H-infinity OPTIMIZATION IN FAULT DETECTION OF UAVs 期刊论文 INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2018, 卷号: 28, 页码: 349-362 作者:  Liu, Hai;  Zhong, Maiying;  Yang, Rui 收藏  |  浏览/下载：11/0  |  提交时间：2019/12/30 fault detection(FD)  H-i/H-infinity optimization  disturbance compensation  unmanned aerial vehicle (UAV)   Anti-Vibration Hammer Detection in UAV Image 其他 2017-01-01 作者:  Yang Heng;  Guo Tao;  Shen Ping;  Chen Fengxiang;  Wang Wei 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/05 anti-vibration hammer  defect detection  R-CNN  unmanned aerial vehicle (UAV)  inspection  deep learning   Anti-Vibration Hammer Detection in UAV Image 其他 2017-01-01 作者:  Yang Heng;  Guo Tao;  Shen Ping;  Chen Fengxiang;  Wang Wei 收藏  |  浏览/下载：5/0  |  提交时间：2019/12/05 anti-vibration hammer  defect detection  R-CNN  unmanned aerial vehicle (UAV)  inspection  deep learning