We present a machine-learning approach to detect and analyze meteor echoes (MADAME), which is a radar data processing workflow featuring advanced machine-learning techniques using both supervised and unsupervised learning. Our results demonstrate that YOLOv4, a convolutional neural network (CNN)-based one-stage object detection model, performs remarkably well in detecting and identifying meteor head and trail echoes within processed radar signals. The detector can identify more than 80 echoes per minute in the testing data obtained from the Jicamarca high power large aperture (HPLA) radar. MADAME is also capable of autonomously processing data in an interferometer mode, as well as determining the target’s radiant source and vector velocity. In the testing data, the Eta Aquarids meteor shower could be clearly identified from the meteor radiant source distribution analyzed automatically by MADAME, thereby demonstrating the proposed algorithm’s functionality. In addition, MADAME found that about 50 percent of the meteors were traveling in inclined and near-inclined circular orbits. Furthermore, meteor head echoes with a trail are more likely to originate from shower meteor sources. Our results highlight the capability of advanced machine-learning techniques in radar signal processing, providing an efficient and powerful tool to facilitate future and new meteor research.
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Mesospheric anomalous diffusion during noctilucent cloud scenarios
Abstract. The Andenes specular meteor radar shows meteor trail diffusion rates increasing on average byabout 10 % at times and locations where a lidar observes noctilucentclouds (NLCs). This high-latitude effect has been attributed to the presenceof charged NLC after exploring possible contributions from thermal tides. Tomake this claim, the current study evaluates data from three stations athigh, middle, and low latitudes for the years 2012 to 2016 to show that NLCinfluence on the meteor trail diffusion is independent of thermal tides. Theobservations also show that the meteor trail diffusion enhancement during NLCcover exists only at high latitudes and near the peaks of NLC layers. Thispaper discusses a number of possible explanations for changes in the regionswith NLCs and leans towards the hypothesis that the relative abundance ofbackground electron density plays the leading role. A more accurate model ofthe meteor trail diffusion around NLC particles would help researchersdetermine mesospheric temperature and neutral density profiles from meteorradars at high latitudes.
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- Award ID(s):
- 1755350
- PAR ID:
- 10176983
- Date Published:
- Journal Name:
- Atmospheric Chemistry and Physics
- Volume:
- 19
- Issue:
- 7
- ISSN:
- 1680-7324
- Page Range / eLocation ID:
- 5259 to 5267
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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