{"title":"罗马尼亚首个地基空间跟踪雷达获取的空间目标数据集","authors":"Călin Bîră, Alexandru Rusu-Casandra","doi":"10.1109/comm54429.2022.9817333","DOIUrl":null,"url":null,"abstract":"Raw spatial-objects radar data is scarce and hard to obtain, obstructing simulations and making improvements to the processing pipeline rather difficult. We provide such a radar dataset of five spatial objects, acquired using the Romania's first spatial-object tracking radar, the Cheia Radar. The dataset contains the tracking of five different objects for a few minutes, using 125W transmitting power and a 2-channel 16-bit 100MSa/s ADC for the receiver end. The input conditions/TLE and the output data format are described; the digital processing pipeline used to extract relevant data is specified so that other researchers may easily use the dataset, which is available on Microsoft Sharepoint.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"335 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Dataset of Spatial Objects Acquired using Romania's First Ground-Based Space Tracking Radar\",\"authors\":\"Călin Bîră, Alexandru Rusu-Casandra\",\"doi\":\"10.1109/comm54429.2022.9817333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Raw spatial-objects radar data is scarce and hard to obtain, obstructing simulations and making improvements to the processing pipeline rather difficult. We provide such a radar dataset of five spatial objects, acquired using the Romania's first spatial-object tracking radar, the Cheia Radar. The dataset contains the tracking of five different objects for a few minutes, using 125W transmitting power and a 2-channel 16-bit 100MSa/s ADC for the receiver end. The input conditions/TLE and the output data format are described; the digital processing pipeline used to extract relevant data is specified so that other researchers may easily use the dataset, which is available on Microsoft Sharepoint.\",\"PeriodicalId\":118077,\"journal\":{\"name\":\"2022 14th International Conference on Communications (COMM)\",\"volume\":\"335 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 14th International Conference on Communications (COMM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/comm54429.2022.9817333\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Communications (COMM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/comm54429.2022.9817333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dataset of Spatial Objects Acquired using Romania's First Ground-Based Space Tracking Radar
Raw spatial-objects radar data is scarce and hard to obtain, obstructing simulations and making improvements to the processing pipeline rather difficult. We provide such a radar dataset of five spatial objects, acquired using the Romania's first spatial-object tracking radar, the Cheia Radar. The dataset contains the tracking of five different objects for a few minutes, using 125W transmitting power and a 2-channel 16-bit 100MSa/s ADC for the receiver end. The input conditions/TLE and the output data format are described; the digital processing pipeline used to extract relevant data is specified so that other researchers may easily use the dataset, which is available on Microsoft Sharepoint.