Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

被引:0
|
作者
Ling Yang
Yun Wang
Zhongke Wang
Qian Yang
Xingang Fan
Fa Tao
Xiaoqiong Zhen
Zhipeng Yang
机构
[1] Chengdu University of Information Technology,Electronic Engineering College
[2] Chengdu University of Information Technology,Information Security Engineering College
[3] Western Kentucky University,Department of Geography and Geology
[4] Chinese Academy of Sciences,Institute of Atmospheric Physics
[5] Chengdu University of Information Technology,CMA Key Laboratory of Atmospheric Sounding
[6] Nanjing University of Information Science and Technology,Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters
[7] CMA,Meteorological Observation Centre
来源
关键词
millimeter-wave cloud radar; clear-air echoes; neural network; laser ceilometer; all-sky camera; feature extraction; feature selection; 毫米波云雷达; 晴空回波; 神经网络; 激光云高仪; 全天空成像仪; 特征提取; 特征选择;
D O I
暂无
中图分类号
学科分类号
摘要
Millimeter-wave cloud radar (MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate, and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.
引用
收藏
页码:912 / 924
页数:12
相关论文
共 50 条
  • [41] Person Identification With Millimeter-Wave Radar in Realistic Smart Home Scenarios
    Xia, Zhaoyang
    Ding, Genming
    Wang, Hui
    Xu, Feng
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [42] Spectrum-Based Hand Gesture Recognition Using Millimeter-Wave Radar Parameter Measurements
    Liu, Changjiang
    Li, Yuanhao
    Ao, Dongyang
    Tian, Haiyan
    IEEE ACCESS, 2019, 7 : 79147 - 79158
  • [43] Automatic measurement system of ATR millimeter-wave radar target's signature
    Xiao, HT
    Zhuang, ZW
    Guo, XH
    He, SH
    Ji, KF
    Xu, F
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 1998, 17 (04) : 262 - 266
  • [44] Foreign Object Debris Automatic Target Detection for Millimeter-Wave Surveillance Radar
    Qin, Fei
    Bu, Xiangxi
    Liu, Yunlong
    Liang, Xingdong
    Xin, Jihao
    SENSORS, 2021, 21 (11)
  • [45] Activity Recognition Based on Millimeter-Wave Radar by Fusing Point Cloud and Range-Doppler Information
    Huang, Yuchen
    Li, Wei
    Dou, Zhiyang
    Zou, Wantong
    Zhang, Anye
    Li, Zan
    SIGNALS, 2022, 3 (02): : 266 - 283
  • [46] Comparative research of cloud boundary heights based on millimeter-wave radar, radio occultation and radiosonde data
    Yan Wei
    Han Ding
    Zhao Xian-Bin
    Zhou Xiao-Ke
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2012, 55 (07): : 2212 - 2226
  • [47] Human Sleep Posture Recognition Based on Millimeter-Wave Radar
    Zhou, Tao
    Xia, Zhaoyang
    Wang, Xiangfeng
    Xu, Feng
    2021 SIGNAL PROCESSING SYMPOSIUM (SPSYMPO), 2021, : 316 - 321
  • [48] mmHSV: In-Air Handwritten Signature Verification via Millimeter-Wave Radar
    Li, Wanqing
    He, Tongtong
    Jing, Nan
    Wang, Lin
    ACM TRANSACTIONS ON INTERNET OF THINGS, 2023, 4 (04):
  • [49] Millimeter Wave Radar-based Plasma Measurements
    Schulz, Christian
    Baer, Christoph
    Fiebrandt, Marcel
    PROCEEDINGS OF THE 2019 IEEE ASIA-PACIFIC MICROWAVE CONFERENCE (APMC), 2019, : 756 - 758
  • [50] Wave Height Estimation Based on the Phase Time Series of Millimeter-Wave Radar
    Zeng, Yuming
    Song, Chunyi
    Xu, Zhiwei
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19