Simulation and Detection of Unintended Electromagnetic Emissions From Super-Regenerative Receivers

A novel method for detecting the presence of the unintended electromagnetic emissions (UEE) from radio receivers is examined without a priori data or training. As an extension of previous research, the behavior of the super-regenerative receiver (SRR) is modeled and simulated with fractional Brownian noise to verify the detection model. This model shows that the presence of noise in the feedback circuit of the SRR is responsible for the characteristic frequency distribution of the receiver's UEE. A second-order self-similarity model is used to estimate the Hurst parameter as a detection threshold for the presence of long-range dependent noise that is a characteristic of the SRR feedback circuit. The method is compared to a typical threshold method and is shown to be a significant improvement in the accuracy of detection.

[1]  F. Xavier Moncunill-Geniz,et al.  A generic approach to the theory of superregenerative reception , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[2]  A. Selamat,et al.  Continuous LoSS detection using iterative window based On SOSS model and MLS approach , 2008, 2008 International Conference on Computer and Communication Engineering.

[3]  P Ferrari,et al.  Introducing the Wireless Ultra Smart Sensor , 2009, 2009 IEEE Instrumentation and Measurement Technology Conference.

[4]  Ali Selamat,et al.  LoSS Detection Approach Based on ESOSS and ASOSS Models , 2008, 2008 The Fourth International Conference on Information Assurance and Security.

[5]  Sarangapani Jagannathan,et al.  Detection of unintended electromagnetic emissions from super-regenerative receivers , 2011, Defense + Commercial Sensing.

[6]  Wendy Van Moer,et al.  Automatic Detection, Estimation, and Validation of Harmonic Components in Measured Power Spectra: All-in-One Approach , 2011, IEEE Transactions on Instrumentation and Measurement.

[7]  H. Sekiguchi,et al.  Proposal of an Information Signal Measurement Method in Display Image Contained in Electromagnetic Noise Emanated from a Personal Computer , 2008, 2008 IEEE Instrumentation and Measurement Technology Conference.

[8]  Daryl G. Beetner,et al.  A Practical Superheterodyne-Receiver Detector Using Stimulated Emissions , 2011, IEEE Transactions on Instrumentation and Measurement.

[9]  D.G. Beetner,et al.  Neural network detection and identification of electronic devices based on their unintended emissions , 2005, 2005 International Symposium on Electromagnetic Compatibility, 2005. EMC 2005..

[10]  Houssain Kettani,et al.  A novel approach to the estimation of the long-range dependence parameter , 2006, IEEE Transactions on Circuits and Systems II: Express Briefs.

[11]  D. Leenaerts.  Chaotic behavior in super regenerative detectors , 1996 .

[12]  Donald J. Brown.  COWLES FOUNDATION FOR RESEARCH IN ECONOMICS , 1999 .

[13]  Sarangapani Jagannathan,et al.  Detection and localization of multiple R/C electronic devices using array detectors , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.