{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:33:42Z","timestamp":1774449222015,"version":"3.50.1"},"reference-count":90,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T00:00:00Z","timestamp":1619308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["328214"],"award-info":[{"award-number":["328214"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["328226"],"award-info":[{"award-number":["328226"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000128188\/19\/NL\/FE"],"award-info":[{"award-number":["4000128188\/19\/NL\/FE"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Radio frequency fingerprinting (RFF) methods are becoming more and more popular in the context of identifying genuine transmitters and distinguishing them from malicious or non-authorized transmitters, such as spoofers and jammers. RFF approaches have been studied to a moderate-to-great extent in the context of non-GNSS transmitters, such as WiFi, IoT, or cellular transmitters, but they have not yet been addressed much in the context of GNSS transmitters. In addition, the few RFF-related works in GNSS context are based on post-correlation or navigation data and no author has yet addressed the RFF problem in GNSS with pre-correlation data. Moreover, RFF methods in any of the three domains (pre-correlation, post-correlation, or navigation) are still hard to be found in the context of GNSS. The goal of this paper was two-fold: first, to provide a comprehensive survey of the RFF methods applicable in the GNSS context; and secondly, to propose a novel RFF methodology for spoofing detection, with a focus on GNSS pre-correlation data, but also applicable in a wider context. In order to support our proposed methodology, we qualitatively investigated the capability of different methods to be used in the context of pre-correlation sampled GNSS data, and we present a simulation-based example, under ideal noise conditions, of how the feature down selection can be done. We are also pointing out which of the transmitter features are likely to play the biggest roles in the RFF in GNSS, and which features are likely to fail in helping RFF-based spoofing detection.<\/jats:p>","DOI":"10.3390\/s21093012","type":"journal-article","created":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T22:31:39Z","timestamp":1619389899000},"page":"3012","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Survey of Spoofer Detection Techniques via Radio Frequency Fingerprinting with Focus on the GNSS Pre-Correlation Sampled Data"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4319-4103","authenticated-orcid":false,"given":"Wenbo","family":"Wang","sequence":"first","affiliation":[{"name":"Electrical Engineering Unit, Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3619-6175","authenticated-orcid":false,"given":"Ignacio","family":"Aguilar Sanchez","sequence":"additional","affiliation":[{"name":"European Space Agency, European Space Research and Technology Centre, 2201 AZ Noordwijk, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3331-6899","authenticated-orcid":false,"given":"Gianluca","family":"Caparra","sequence":"additional","affiliation":[{"name":"European Space Agency, European Space Research and Technology Centre, 2201 AZ Noordwijk, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9265-5781","authenticated-orcid":false,"given":"Andy","family":"McKeown","sequence":"additional","affiliation":[{"name":"GMV-NSL, Nottingham, NG7 2TU, UK"}]},{"given":"Tim","family":"Whitworth","sequence":"additional","affiliation":[{"name":"GMV-NSL, Nottingham, NG7 2TU, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1718-6924","authenticated-orcid":false,"given":"Elena Simona","family":"Lohan","sequence":"additional","affiliation":[{"name":"Electrical Engineering Unit, Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rehman, S., Sowerby, K., Alam, S., and Ardekani, I. (2014, January 29\u201331). Radio frequency fingerprinting and its challenges. Proceedings of the 2014 IEEE Conference on Communications and Network Security, San Francisco, CA, USA.","DOI":"10.1109\/CNS.2014.6997522"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1538728","DOI":"10.1155\/2017\/1538728","article-title":"Radio Frequency Fingerprint Extraction Based on Multidimension Permutation Entropy","volume":"2017","author":"Deng","year":"2017","journal-title":"Int. J. Antennas Propag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Morales-Ferre, R., Wang, W., Sanz-Abia, A., and Lohan, E.S. (2020). Identifying GNSS Signals Based on Their Radio Frequency (RF) Features\u2014A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator. Data, 5.","DOI":"10.3390\/data5010018"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bassey, J., Li, X., and Qian, L. (2020). Device Authentication Codes based on RF Fingerprinting using Deep Learning. arXiv.","DOI":"10.1109\/FMEC.2019.8795319"},{"key":"ref_5","first-page":"202","article-title":"Influence of a radio frequency on RF fingerprinting accuracy based on ray tracing simulation","volume":"2013","author":"Wozmca","year":"2013","journal-title":"Eurocon"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Greenberg, E., and Levy, P. (2017, January 19\u201324). Propagation aspects for RF fingerprinting at open areas over irregular terrain. Proceedings of the 2017 11th European Conference on Antennas and Propagation (EUCAP), Paris, France.","DOI":"10.23919\/EuCAP.2017.7928080"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kalayci, A.O., and Akdem\u0130r, E. (2018, January 2\u20135). RF fingerprinting based indoor localization for uncooperative emitters. Proceedings of the 2018 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey.","DOI":"10.1109\/SIU.2018.8404253"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Khandker, S., Torres-Sospedra, J., and Ristaniemi, T. (2019). Improving RF Fingerprinting Methods by Means of D2D Communication Protocol. Electronics, 8.","DOI":"10.3390\/electronics8010097"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.jcss.2013.06.013","article-title":"Analysis of impersonation attacks on systems using RF fingerprinting and low-end receivers","volume":"80","author":"Rehman","year":"2014","journal-title":"J. Comput. Syst. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Thoelert, S., Steigenberger, P., Montenbruck, O., and Meurer, M. (2019, January 16\u201319). GPS III Arrived\u2013An Initial Analysis of Signal Payload and Achieved User Performance. Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation, Miami, FL, USA.","DOI":"10.33012\/2019.17043"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1109\/COMST.2019.2949178","article-title":"A Survey on Coping With Intentional Interference in Satellite Navigation for Manned and Unmanned Aircraft","volume":"22","author":"Richter","year":"2020","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Rustamov, A., Gogoi, N., Minetto, A., and Dovis, F. (2020, January 2\u20134). Assessment of the Vulnerability to Spoofing Attacks of GNSS Receivers Integrated in Consumer Devices. Proceedings of the 2020 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland.","DOI":"10.1109\/ICL-GNSS49876.2020.9115489"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2287","DOI":"10.1109\/TIM.2019.2923485","article-title":"Performance of EGNSS-Based Timing in Various Threat Conditions","volume":"69","author":"Honkala","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Issam, S.M., Adnane, A., and Madiabdessalam, A. (2020, January 2\u20133). Anti-Jamming techniques for aviation GNSS-based navigation systems: Survey. Proceedings of the 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), Kenitra, Morocco.","DOI":"10.1109\/ICECOCS50124.2020.9314449"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Nicola, M., Falco, G., Ferre, R.M., Lohan, E.S., de la Fuente, A., and Falletti, E. (2020). Collaborative Solutions for Interference Management in GNSS-Based Aircraft Navigation. Sensors, 20.","DOI":"10.3390\/s20154085"},{"key":"ref_16","unstructured":"Caparra, G. (2021, April 24). Authentication and Integrity Protection at Data and Physical Layer for Critical Infrastructures. Available online: paduaresearch.cab.unipd.it\/9797\/1\/tesi_Gianluca_Caparra.pdf."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Caparra, G., Ceccato, S., Laurenti, N., and Cramer, J. (2017, January 25\u201329). Feasibility and Limitations of Self-Spoofing Attacks on GNSS Signals with Message Authentication. Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+), Portland, OR, USA.","DOI":"10.33012\/2017.15402"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"165444","DOI":"10.1109\/ACCESS.2020.3022294","article-title":"Spoofing and Anti-Spoofing Technologies of Global Navigation Satellite System: A Survey","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1258","DOI":"10.1109\/JPROC.2016.2526658","article-title":"GNSS Spoofing and Detection","volume":"104","author":"Psiaki","year":"2016","journal-title":"Proc. IEEE"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2897166","article-title":"A Survey and Analysis of the GNSS Spoofing Threat and Countermeasures","volume":"48","author":"Schmidt","year":"2016","journal-title":"ACM Comput. Surv."},{"key":"ref_21","first-page":"2120","article-title":"Feature selection for GNSS receiver fingerprinting","volume":"17","author":"Borio","year":"2017","journal-title":"InsideGNSS"},{"key":"ref_22","unstructured":"Kuciapinski, K.S., Temple, M.A., and Klein, R.W. (2010, January 26\u201328). ANOVA-based RF DNA analysis: Identifying significant parameters for device classification. Proceedings of the 2010 International Conference on Wireless Information Networks and Systems (WINSYS), Athens, Greece."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2379776.2379782","article-title":"On Physical-Layer Identification of Wireless Devices","volume":"45","author":"Danev","year":"2012","journal-title":"ACM Comput. Surv."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Baldini, G., Giuliani, R., Steri, G., and Neisse, R. (2017, January 6\u20139). Physical layer authentication of Internet of Things wireless devices through permutation and dispersion entropy. Proceedings of the 2017 Global Internet of Things Summit (GIoTS), Geneva, Switzerland.","DOI":"10.1109\/GIOTS.2017.8016272"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1049\/el.2018.6229","article-title":"Comparison of techniques for radiometric identification based on deep convolutional neural networks","volume":"55","author":"Baldini","year":"2019","journal-title":"Electron. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"17100","DOI":"10.1109\/ACCESS.2021.3053491","article-title":"Identification of OFDM-Based Radios Under Rayleigh Fading Using RF-DNA and Deep Learning","volume":"9","author":"Fadul","year":"2021","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Broumandan, A., and Lachapelle, G. (2018). Spoofing Detection Using GNSS\/INS\/Odometer Coupling for Vehicular Navigation. Sensors, 18.","DOI":"10.3390\/s18051305"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Lo, S., Chen, Y.H., Jain, H., and Enge, P. (2018, January 24\u201328). Robust GNSS Spoof Detection using Direction of Arrival: Methods and Practice. Proceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), Miami, FL, USA.","DOI":"10.33012\/2018.15900"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nguyen, V.H., Falco, G., Falletti, E., and Nicola, M. (2018, January 5\u20137). A Dual Antenna GNSS Spoofing Detector Based on the Dispersion of Double Difference Measurements. Proceedings of the 2018 9th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), Noordwijk, The Netherlands.","DOI":"10.1109\/NAVITEC.2018.8642705"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1109\/TST.2013.6678905","article-title":"Intermediate spoofing strategies and countermeasures","volume":"18","author":"Gao","year":"2013","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9459","DOI":"10.1109\/ACCESS.2016.2587322","article-title":"Performance Evaluation of Multimodal Detection Method for GNSS Intermediate Spoofing","volume":"4","author":"Li","year":"2016","journal-title":"IEEE Access"},{"key":"ref_32","first-page":"28","article-title":"Assessing the spoofing threat","volume":"20","author":"Humphreys","year":"2018","journal-title":"GPS World"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4224","DOI":"10.1109\/TAES.2020.2990149","article-title":"A GPS Spoofing Detection and Classification Correlator-Based Technique Using the LASSO","volume":"56","author":"Schmidt","year":"2020","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Falletti, E., Motella, B., and Gamba, M.T. (September, January 29). Post-correlation signal analysis to detect spoofing attacks in GNSS receivers. Proceedings of the 2016 24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary.","DOI":"10.1109\/EUSIPCO.2016.7760408"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Thombre, S., Raasakka, J., Hurskainen, H., Nurmi, J., Valkama, M., and Lohan, S. (2011, January 29\u201330). Local oscillator phase noise effects on phase angle component of GNSS code correlation. Proceedings of the 2011 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland.","DOI":"10.1109\/ICL-GNSS.2011.5955271"},{"key":"ref_36","unstructured":"Psiaki, M.L., Powell, S.P., and O\u2019hanlon, B.W. (2013, January 16\u201320). GNSS Spoofing Detection using High-Frequency Antenna Motion and Carrier-Phase Data. Proceedings of the 26th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2013), Nashville, TN, USA."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Calero, D., and Fernandez, E. (2015, January 20\u201323). Characterization of Chip-Scale Atomic Clock for GNSS navigation solutions. Proceedings of the 2015 International Association of Institutes of Navigation World Congress (IAIN), Prague, Czech Republic.","DOI":"10.1109\/IAIN.2015.7352264"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Fernandez, E., Calero, D., and Pares, M.E. (2017). CSAC Characterization and Its Impact on GNSS Clock Augmentation Performance. Sensors, 17.","DOI":"10.3390\/s17020370"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1109\/TAES.2018.2816878","article-title":"Design Realization and Tests of a Space-Borne GaN Solid State Power Amplifier for Second Generation Galileo Navigation System","volume":"54","author":"Giofre","year":"2018","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1007\/s10291-014-0407-3","article-title":"Spoofing detection, classification and cancelation (SDCC) receiver architecture for a moving GNSS receiver","volume":"19","author":"Broumandan","year":"2015","journal-title":"GPS Solut."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1109\/78.950789","article-title":"Advanced methods for I\/Q imbalance compensation in communication receivers","volume":"49","author":"Valkama","year":"2001","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/TIM.2009.2025989","article-title":"Receiver I\/Q Imbalance: Tone Test, Sensitivity Analysis, and the Universal Software Radio Peripheral","volume":"59","author":"Handel","year":"2010","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2854","DOI":"10.1109\/TIM.2010.2046649","article-title":"Modeling DAC Output Waveforms","volume":"59","author":"Liccardo","year":"2010","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"132413","DOI":"10.1109\/ACCESS.2019.2940515","article-title":"Time-Domain Evaluation Method for Clock Frequency Stability Based on Precise Point Positioning","volume":"7","author":"Lei","year":"2019","journal-title":"IEEE Access"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Chen, X., Peng, C., Huan, H., Nian, F., and Yang, B. (2019). Measuring the Power Law Phase Noise of an RF Oscillator with a Novel Indirect Quantitative Scheme. Electronics, 8.","DOI":"10.3390\/electronics8070767"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Gomez-Casco, D., Lopez-Salcedo, J.A., and Seco-Granados, G. (2016, January 26\u201329). Generalized integration techniques for high-sensitivity GNSS receivers affected by oscillator phase noise. Proceedings of the 2016 IEEE Statistical Signal Processing Workshop (SSP), Palma de Mallorca, Spain.","DOI":"10.1109\/SSP.2016.7551809"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Zhang, S., Wang, X., Wang, H., and Yang, J. (2010, January 13\u201316). From Allan variance to phase noise: A new conversion approach. Proceedings of the EFTF-2010 24th European Frequency and Time Forum, Noordwijk, The Netherlands.","DOI":"10.1109\/EFTF.2010.6533711"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1109\/TCOMM.2014.011114.130094","article-title":"Analysis of the Power Amplifier Nonlinearity on the Power Allocation in Cognitive Radio Networks","volume":"62","author":"Majidi","year":"2014","journal-title":"IEEE Trans. Commun."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Schreurs, D., O\u2019Droma, M., Goacher, A.A., and Gadringer, M. (2008). RF Power Amplifier Behavioral Modeling, Cambridge University Press.","DOI":"10.1017\/CBO9780511619960"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1049\/el:20010940","article-title":"Digital predistortion of wideband signals based on power amplifier model with memory","volume":"37","author":"Kim","year":"2001","journal-title":"Electron. Lett."},{"key":"ref_51","unstructured":"OHB System AG- Galileo -European Satellite Navigation System (Space Segment) (2021, February 20). OHB Brochure. Available online: https:\/\/www.ohb-system.de\/files\/images\/mediathek\/downloads\/190603_OHB-System_Galileo_FOC-Satellites_2019-05.pdf."},{"key":"ref_52","unstructured":"National Instruments Corp (2021, April 24). Global Synchronization and Clock Disciplining with NI USRP-293x Software Defined Radio. Available online: https:\/\/www.ni.com\/fi-fi\/innovations\/white-papers\/20\/global-synchronization-and-clock-disciplining-with-ni-usrp-293x-.html."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Rehman, S.U., Sowerby, K.W., Alam, S., Ardekani, I.T., and Komosny, D. (2015, January 7\u201310). Effect of channel impairments on radiometric fingerprinting. Proceedings of the 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/ISSPIT.2015.7394371"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Kennedy, I.O., and Kuzminskiy, A.M. (2010, January 19\u201322). RF Fingerprint detection in a wireless multipath channel. Proceedings of the 2010 7th International Symposium on Wireless Communication Systems, York, UK.","DOI":"10.1109\/ISWCS.2010.5624371"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Zheng, T., Sun, Z., and Ren, K. (May, January 29). FID: Function Modeling-based Data-Independent and Channel-Robust Physical-Layer Identification. Proceedings of the IEEE INFOCOM 2019-IEEE Conference on Computer Communications, Paris, France.","DOI":"10.1109\/INFOCOM.2019.8737597"},{"key":"ref_56","unstructured":"Tascioglu, S., Kose, M., and Telatar, Z. (December, January 30). Effect of sampling rate on transient based RF fingerprinting. Proceedings of the 2017 10th International Conference on Electrical and Electronics Engineering (ELECO), Bursa, Turkey."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Ur Rehman, S., Sowerby, K., and Coghill, C. (February, January 30). RF fingerprint extraction from the energy envelope of an instantaneous transient signal. Proceedings of the 2012 Australian Communications Theory Workshop (AusCTW), Wellington, New Zealand.","DOI":"10.1109\/AusCTW.2012.6164912"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LCOMM.2002.807439","article-title":"Subchip multipath delay estimation for downlink WCDMA system based on Teager-Kaiser operator","volume":"7","author":"Hamila","year":"2003","journal-title":"IEEE Commun. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"3603","DOI":"10.1109\/TSP.2020.2995972","article-title":"Digital predistortion for multiuser hybrid MIMO at mmWaves","volume":"68","author":"Brihuega","year":"2020","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_60","unstructured":"Rasmussen, K.B., and Capkun, S. (2007, January 17\u201321). Implications of Radio Fingerprinting on the Security of Sensor Networks. Proceedings of the 2007 Third International Conference on Security and Privacy in Communications Networks and the Workshops\u2014SecureComm 2007, Nice, France."},{"key":"ref_61","unstructured":"Gahlawat, S. (2020). Investigation of RF Fingerprinting Approaches in GNSS. [Ph.D. Thesis, Tampere University]."},{"key":"ref_62","unstructured":"Hall, J., Barbeau, M., and Kranakis, E. (2003, January 14\u201316). Detection Of Transient In Radio Frequency Fingerprinting Using Signal Phase. Proceedings of the IASTED International Conference on Wireless and Optical Communications, Banff, AL, Canada."},{"key":"ref_63","unstructured":"Gerdes, R.M., Daniels, T.E., Mina, M., and Russell, S.F. (2006, January 23\u201326). Device identification via analog signal fingerprinting: A matched filter approach. Proceedings of the Network and Distributed System Security Symposium NDSS, San Diego, CA, USA."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Brik, V., Banerjee, S., and Gruteser, M. (2008, January 8\u201312). Wireless device identification with radiometric signatures. Proceedings of the 14th ACM international conference on mobile computing and networking, ser. MobiCom \u201908, San Francisco, CA, USA.","DOI":"10.1145\/1409944.1409959"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Candore, A., Kocabas, O., and Koushanfar, F. (2009, January 27). Robust stable radiometric fingerprinting for wireless devices. Proceedings of the 2009 IEEE International Workshop on Hardware-Oriented Security and Trust, San Francisco, CA, USA.","DOI":"10.1109\/HST.2009.5224969"},{"key":"ref_66","unstructured":"Huang, Y., and Zheng, H. (2012, January 15\u201317). Radio frequency fingerprinting based on the constellation errors. Proceedings of the 2012 18th Asia-Pacific Conference on Communications (APCC), Jeju, Korea."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1049\/el.2015.0051","article-title":"Classification performance using \u2018RF-DNA\u2019 fingerprinting of ultra-wideband noise waveforms","volume":"51","author":"Lukacs","year":"2015","journal-title":"Electron. Lett."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Borio, D., Gioia, C., Baldini, G., and Fortuny, J. (2016, January 12\u201316). GNSS Receiver Fingerprinting for Security-Enhanced Applications. Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+), Portland, OR, USA.","DOI":"10.33012\/2016.14688"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Jia, Y., Zhu, S., and Gan, L. (2017). Specific Emitter Identification Based on the Natural Measure. Entropy, 19.","DOI":"10.3390\/e19030117"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"De Wilde, W., Sleewaegen, J.M., Bougard, B., Cuypers, G., Popugaev, A., Landmann, M., Schirmer, C., Roca, D.E., L\u00f3pez-Salcedo, J.A., and Granados, G.S. (2018, January 24\u201328). Authentication by Polarization: A Powerful Anti-Spoofing Method. Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+), Miami, FL, USA.","DOI":"10.33012\/2018.15917"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Ali, A., and Fischer, G. (2019, January 16\u201318). Symbol Based Statistical RF Fingerprinting for Fake Base Station Identification. Proceedings of the 2019 29th International Conference Radioelektronika (RADIOELEKTRONIKA), Pardubice, Czech Republic.","DOI":"10.1109\/RADIOELEK.2019.8733585"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Ali, A., and Fischer, G. (2019, January 8\u20139). The Phase Noise and Clock Synchronous Carrier Frequency Offset based RF Fingerprinting for the Fake Base Station Detection. Proceedings of the 2019 IEEE 20th Wireless and Microwave Technology Conference (WAMICON), Cocoa Beach, FL, USA.","DOI":"10.1109\/WAMICON.2019.8765471"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"103291","DOI":"10.1109\/ACCESS.2019.2929311","article-title":"Feature Reduction Method for Cognition and Classification of IoT Devices Based on Artificial Intelligence","volume":"7","author":"Chen","year":"2019","journal-title":"IEEE Access"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Hanna, S.S., and Cabric, D. (2019, January 18\u201321). Deep Learning Based Transmitter Identification using Power Amplifier Nonlinearity. Proceedings of the 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA.","DOI":"10.1109\/ICCNC.2019.8685569"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"54425","DOI":"10.1109\/ACCESS.2019.2913759","article-title":"Specific Emitter Identification Based on Deep Residual Networks","volume":"7","author":"Pan","year":"2019","journal-title":"IEEE Access"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Zha, H., Tian, Q., and Lin, Y. (2020, January 13\u201316). Real-World ADS-B signal recognition based on Radio Frequency Fingerprinting. Proceedings of the 2020 IEEE 28th International Conference on Network Protocols (ICNP), Madrid, Spain.","DOI":"10.1109\/ICNP49622.2020.9259404"},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Nicolussi, A., Tanner, S., and Wattenhofer, R. (2021, January 18\u201321). Aircraft Fingerprinting Using Deep Learning. Proceedings of the 2020 28th European Signal Processing Conference (EUSIPCO), Amsterdam, The Netherlands.","DOI":"10.23919\/Eusipco47968.2020.9287691"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1109\/OJCOMS.2019.2955889","article-title":"Detection and Classification of UAVs Using RF Fingerprints in the Presence of Wi-Fi and Bluetooth Interference","volume":"1","author":"Ezuma","year":"2020","journal-title":"IEEE Open J. Commun. Soc."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Weng, L., Peng, J., Li, J., and Zhu, Y. (2020, January 9\u201311). Message Structure Aided Attentional Convolution Network for RF Device Fingerprinting. Proceedings of the 2020 IEEE\/CIC International Conference on Communications in China (ICCC), Chongqing, China.","DOI":"10.1109\/ICCC49849.2020.9238868"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Reising, D., Cancelleri, J., Loveless, T.D., Kandah, F., and Skjellum, A. (2020). Radio Identity Verification-based IoT Security Using RF-DNA Fingerprints and SVM. IEEE Internet Things J., 1.","DOI":"10.1109\/JIOT.2020.3045305"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Soltani, N., Reus-Muns, G., Salehihikouei, B., Dy, J., Ioannidis, S., and Chowdhury, K. (2020). RF Fingerprinting Unmanned Aerial Vehicles with Non-standard Transmitter Waveforms. IEEE Trans. Veh. Technol., 69.","DOI":"10.1109\/TVT.2020.3042128"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Zhou, X., Hu, A., Li, G., Peng, L., Xing, Y., and Yu, J. (2021). A Robust Radio Frequency Fingerprint Extraction Scheme for Practical Device Recognition. IEEE Internet Things J., 1.","DOI":"10.1109\/JIOT.2021.3051402"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"2177","DOI":"10.1109\/78.218145","article-title":"Transient signal detection using prior information in the likelihood ratio test","volume":"41","author":"Frisch","year":"1993","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1109\/TAES.1986.310745","article-title":"An Adaptive Detection Algorithm","volume":"AES-22","author":"Kelly","year":"1986","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Karunaratne, S., Krijestorac, E., and Cabric, D. (2020). Penetrating RF Fingerprinting-Based Authentication with a Generative Adversarial Attack. arXiv.","DOI":"10.1109\/ICC42927.2021.9500893"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1109\/MCOM.2018.1800153","article-title":"Deep learning convolutional neural networks for radio identification","volume":"56","author":"Riyaz","year":"2018","journal-title":"IEEE Commun. Mag."},{"key":"ref_87","unstructured":"Morin, C., Cardoso, L., Hoydis, J., and Gorce, J.M. (2021, April 24). Deep Learning-Based Transmitter Identification on the Physical Layer. INRIA Report. Available online: https:\/\/hal.inria.fr\/hal-03117090."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Ibrahim, Y., Mu\u2019Azu, M.B., Adedokun, A.E., and Sha\u2019Aban, Y.A. (2017, January 7\u201310). A performance analysis of logistic regression and support vector machine classifiers for spoof fingerprint detection. Proceedings of the 2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON), Owerri, Nigeria.","DOI":"10.1109\/NIGERCON.2017.8281872"},{"key":"ref_89","first-page":"33","article-title":"Introduction of Random Forest Classifier to ZigBee Device Network Authentication Using RF-DNA Fingerprinting","volume":"13","author":"Patel","year":"2014","journal-title":"J. Inf. Warf."},{"key":"ref_90","unstructured":"Rebeyrol, E., Macabiau, C., Ries, L., Issler, J.L., Bousquet, M., and Boucheret, M.L. (2006, January 18\u201320). Phase noise in GNSS transmission\/reception system. Proceedings of the 2006 National Technical Meeting of the Institute of Navigation, Monterey, CA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3012\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:52:36Z","timestamp":1760161956000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3012"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,25]]},"references-count":90,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["s21093012"],"URL":"https:\/\/doi.org\/10.3390\/s21093012","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,25]]}}}