{"title":"基于时频和空间滤波的多传感器中频估计","authors":"Nabeel Ali Khan, Sadiq Ali, Ateeq Ur Rehman","doi":"10.1109/ICFTSC57269.2022.10040066","DOIUrl":null,"url":null,"abstract":"Instantaneous frequency (IF) is an important parameter whose accurate estimation is useful in many applications including source localization, blind source separation and signal detection. We propose a computationally efficient and accurate multi-component IF estimator for multi-sensor recordings. The proposed method iteratively estimates the IF of signal components by first tracking the components based on their angle of arrival information and then removing components through time-frequency (TF) and spatial filtering. Experimental results indicate that the proposed method based on joint TF and spatial filtering leads to accurate IF estimates as compared to a recent method that only performs filtering in the TF domain.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-sensor IF Estimation Based on Time-Frequency and Spatial Filtering\",\"authors\":\"Nabeel Ali Khan, Sadiq Ali, Ateeq Ur Rehman\",\"doi\":\"10.1109/ICFTSC57269.2022.10040066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Instantaneous frequency (IF) is an important parameter whose accurate estimation is useful in many applications including source localization, blind source separation and signal detection. We propose a computationally efficient and accurate multi-component IF estimator for multi-sensor recordings. The proposed method iteratively estimates the IF of signal components by first tracking the components based on their angle of arrival information and then removing components through time-frequency (TF) and spatial filtering. Experimental results indicate that the proposed method based on joint TF and spatial filtering leads to accurate IF estimates as compared to a recent method that only performs filtering in the TF domain.\",\"PeriodicalId\":386462,\"journal\":{\"name\":\"2022 International Conference on Future Trends in Smart Communities (ICFTSC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Future Trends in Smart Communities (ICFTSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFTSC57269.2022.10040066\",\"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 International Conference on Future Trends in Smart Communities (ICFTSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFTSC57269.2022.10040066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-sensor IF Estimation Based on Time-Frequency and Spatial Filtering
Instantaneous frequency (IF) is an important parameter whose accurate estimation is useful in many applications including source localization, blind source separation and signal detection. We propose a computationally efficient and accurate multi-component IF estimator for multi-sensor recordings. The proposed method iteratively estimates the IF of signal components by first tracking the components based on their angle of arrival information and then removing components through time-frequency (TF) and spatial filtering. Experimental results indicate that the proposed method based on joint TF and spatial filtering leads to accurate IF estimates as compared to a recent method that only performs filtering in the TF domain.