{"_id":"nAQMinvTCNNZEX33c","bibbaseid":"yen-hioka-mace-estimatingpowerspectraldensityofunmannedaerialvehiclerotornoiseusingmultisensoryinformation-2018","authorIDs":[],"author_short":["Yen, B.","Hioka, Y.","Mace, B."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["B."],"propositions":[],"lastnames":["Yen"],"suffixes":[]},{"firstnames":["Y."],"propositions":[],"lastnames":["Hioka"],"suffixes":[]},{"firstnames":["B."],"propositions":[],"lastnames":["Mace"],"suffixes":[]}],"booktitle":"2018 26th European Signal Processing Conference (EUSIPCO)","title":"Estimating Power Spectral Density of Unmanned Aerial Vehicle Rotor Noise Using Multisensory Information","year":"2018","pages":"2434-2438","abstract":"A method to accurately estimate the power spectral density (PSD) of an unmanned aerial vehicle (UAV) is proposed, in anticipation of being used for a UAV-mounted audio recording system that clearly captures target sound while suppressing rotor noise. The method utilises UAV rotor characteristics as well as microphone recorded signals to combat practical limitations seen in a previous study. The proposed method was evaluated on a simulation platform modelled after the UAV used in the previous study. Results showed that the proposed method was able to estimate the rotor noise PSD to within 1.3-3.3 dB log spectral distortion (LSD) regardless of the presence of surrounding sound sources.","keywords":"autonomous aerial vehicles;density measurement;power measurement;rotors;sensor fusion;unmanned aerial vehicle rotor noise;multisensory information;UAV-mounted audio recording system;UAV rotor characteristics;power spectral density estimation;rotor noise PSD estimation;rotor noise suppression;microphone;signal recording;log spectral distortion;LSD;sound sources;noise figure 1.3 dB to 3.3 dB;Rotors;Unmanned aerial vehicles;Array signal processing;Audio recording;Microphone arrays;Microphone array;unmanned aerial vehicle;source enhancement;power spectral density;rotor noise","doi":"10.23919/EUSIPCO.2018.8553140","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570433053.pdf","bibtex":"@InProceedings{8553140,\n author = {B. Yen and Y. Hioka and B. Mace},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Estimating Power Spectral Density of Unmanned Aerial Vehicle Rotor Noise Using Multisensory Information},\n year = {2018},\n pages = {2434-2438},\n abstract = {A method to accurately estimate the power spectral density (PSD) of an unmanned aerial vehicle (UAV) is proposed, in anticipation of being used for a UAV-mounted audio recording system that clearly captures target sound while suppressing rotor noise. The method utilises UAV rotor characteristics as well as microphone recorded signals to combat practical limitations seen in a previous study. The proposed method was evaluated on a simulation platform modelled after the UAV used in the previous study. Results showed that the proposed method was able to estimate the rotor noise PSD to within 1.3-3.3 dB log spectral distortion (LSD) regardless of the presence of surrounding sound sources.},\n keywords = {autonomous aerial vehicles;density measurement;power measurement;rotors;sensor fusion;unmanned aerial vehicle rotor noise;multisensory information;UAV-mounted audio recording system;UAV rotor characteristics;power spectral density estimation;rotor noise PSD estimation;rotor noise suppression;microphone;signal recording;log spectral distortion;LSD;sound sources;noise figure 1.3 dB to 3.3 dB;Rotors;Unmanned aerial vehicles;Array signal processing;Audio recording;Microphone arrays;Microphone array;unmanned aerial vehicle;source enhancement;power spectral density;rotor noise},\n doi = {10.23919/EUSIPCO.2018.8553140},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570433053.pdf},\n}\n\n","author_short":["Yen, B.","Hioka, Y.","Mace, B."],"key":"8553140","id":"8553140","bibbaseid":"yen-hioka-mace-estimatingpowerspectraldensityofunmannedaerialvehiclerotornoiseusingmultisensoryinformation-2018","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570433053.pdf"},"keyword":["autonomous aerial vehicles;density measurement;power measurement;rotors;sensor fusion;unmanned aerial vehicle rotor noise;multisensory information;UAV-mounted audio recording system;UAV rotor characteristics;power spectral density estimation;rotor noise PSD estimation;rotor noise suppression;microphone;signal recording;log spectral distortion;LSD;sound sources;noise figure 1.3 dB to 3.3 dB;Rotors;Unmanned aerial vehicles;Array signal processing;Audio recording;Microphone arrays;Microphone array;unmanned aerial vehicle;source enhancement;power spectral density;rotor noise"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2018url.bib","creationDate":"2021-02-13T15:38:40.213Z","downloads":0,"keywords":["autonomous aerial vehicles;density measurement;power measurement;rotors;sensor fusion;unmanned aerial vehicle rotor noise;multisensory information;uav-mounted audio recording system;uav rotor characteristics;power spectral density estimation;rotor noise psd estimation;rotor noise suppression;microphone;signal recording;log spectral distortion;lsd;sound sources;noise figure 1.3 db to 3.3 db;rotors;unmanned aerial vehicles;array signal processing;audio recording;microphone arrays;microphone array;unmanned aerial vehicle;source enhancement;power spectral density;rotor noise"],"search_terms":["estimating","power","spectral","density","unmanned","aerial","vehicle","rotor","noise","using","multisensory","information","yen","hioka","mace"],"title":"Estimating Power Spectral Density of Unmanned Aerial Vehicle Rotor Noise Using Multisensory Information","year":2018,"dataSources":["yiZioZximP7hphDpY","iuBeKSmaES2fHcEE9"]}