Abstract
Aiming at the shortcomings of the research on individual identification technology of emitters, which is primarily based on theoretical simulation and lack of verification equipment to conduct external field measurements, an emitter individual identification system based on Automatic Dependent Surveillance–Broadcast is designed. On one hand, the system completes the individual feature extraction of the signal preamble. On the other hand, it realizes decoding of the transmitter’s individual identity information and generates an individual recognition training data set, on which we can train the recognition network to achieve individual signal recognition. For the collected signals, six parameters were extracted as individual features. To reduce the feature dimensions, a Bessel curve fitting method is used for four of the features. The spatial distribution of the Bezier curve control points after fitting is taken as an individual feature. The processed features are classified with multiple classifiers, and the classification results are fused using the improved Dempster–Shafer evidence theory. Field measurements show that the average individual recognition accuracy of the system reaches 88.3%, which essentially meets the requirements.
Highlights
IntroductionRadar emitter individual identification can achieve the identification of ‘‘signal-emitter individual,’’ precisely lock the threat sources and high-value targets, which has strong significance in military applications, and has important value in civil network security access, cognitive radio, public security, and other fields
Radar emitter individual identification can achieve the identification of ‘‘signal-emitter individual,’’ precisely lock the threat sources and high-value targets, which has strong significance in military applications, and has important value in civil network security access, cognitive radio, public security, and other fields.A significant number of research institutions worldwide have studied the radar emitter individual recognition technology
Because the 1090-MHz Automatic Dependent Surveillance–Broadcast (ADS-B) signal is a type of secondary radar, it has the characteristics of a pulse signal.[8,9]
Summary
Radar emitter individual identification can achieve the identification of ‘‘signal-emitter individual,’’ precisely lock the threat sources and high-value targets, which has strong significance in military applications, and has important value in civil network security access, cognitive radio, public security, and other fields. Because the 1090-MHz Automatic Dependent Surveillance–Broadcast (ADS-B) signal is a type of secondary radar, it has the characteristics of a pulse signal.[8,9] It is rich in signal resources, and the individual transmitter identity is easy to extract, which can effectively compensate for the above deficiencies. The system first completes the down conversion and acquisition function of the 1090-MHz signal, preprocesses the leading signal pulse, extracts its individual characteristics, decodes the signal, extracts the individual identity information, makes the individual identification data set, transforms the individual identification problem into a standard pattern recognition problem, and uses the data set to achieve supervised pattern recognition to test the performance of the individual feature extraction algorithm of the conventional pulse signal.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Distributed Sensor Networks
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
