Intercept of frequency agility signal using coding Nyquist folding receiver
Author: 
Keyu LongAuthors Info & Claims
Abstract
The parameter estimation of the frequency agility (FA) signal using the coding Nyquist folding receiver (CNYFR) is presented. The estimation algorithm adopting linear frequency modulation (LFM) as the local analogue modulation is derived. The Nyquist zone is estimated by the pseudo Wigner-Ville distribution (PWVD) and the hopping frequencies are calculated by the maximum likelihood (ML) method. Simulations show that CNYFR with analogue modulation of LFM has better performance than the sinusoidal frequency modulation (SFM) one, and the parameter estimation accuracy is acceptable when the SNR is above 0dB.
References
[1]
J. R. Bellegarda, S. V. Maric, E. L. Titlebaum, The hit array: a synthesis tool for multiple access frequency hop signals, IEEE Transactions on Aerospace and Electronic Systems, Vol.29, No.3, 1993, pp.624-635.
[2]
K. Morrison, Effective bandwidth SF-CW SAR increase using frequency agility, IEEE Aerospace and Electronic Systems Magazine, Vol.21, No.6, 2006, pp.28-32.
[3]
K. Becker, Passive localization of frequency-agile radars from angle and frequency measurements, IEEE Transactions on Aerospace and Electronic Systems, Vol.35, No.4, 1999, pp.1129-1144.
[4]
S. R. Rogers, On analytical evaluation of glint error reduction for frequency-hopping radars, IEEE Transactions on Aerospace and Electronic Systems, Vol.27, No.6, 1991, pp. 891-894.
[5]
G. Lellouch, P. Tran, R. Pribic, P. van Genderen, OFDM waveforms for frequency agility and opportunities for doppler processing in radar, IEEE Radar Conference, 2008.
[6]
E. J. Candes, T. Tao, Near-optimal signal recovery from random projections: universal encoding strategies? IEEE Transactions on Information Theory, Vol.52, No.12, 2006, pp. 5406-5425.
[7]
D. L. Donoho, Compressed sensing, IEEE Transactions on Information Theory, Vol.52, No.4, 2006, pp. 1289-1306.
[8]
M. A. Herman, T. Strohmer, High-resolution radar via compressed sensing, IEEE Transactions on Signal Processing, Vol.57, No.6, 2009, pp. 2275-2284.
[9]
J. Ma, Compressed sensing for surface characterization and metrology. IEEE Transactions on Instrumentation and Measurement, Vol.59, No.6, 2010, pp. 1600-1615.
[10]
L. C. Potter, E. Ertin, J. T. Parker, M. Cetin, Sparsity and compressed sensing in radar imaging. IEEE Proceedings, Vol.98, No.6, 2010, pp. 1006-1020.
[11]
J. Provost, F. Lesage, The application of compressed sensing for photo-acoustic tomography. IEEE Transactions on Medical Imaging, Vol.28, No.4, 2009, pp. 585-594.
[12]
P. Flandrin, P. Borgnat, Time-frequency energy distributions meet compressed sensing, IEEE Transactions on Signal Processing, Vol.58, No.6, 2010, pp. 2974-2982.
[13]
J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, R. G. Baraniuk, Beyond Nyquist: efficient sampling of sparse bandlimited signals, IEEE Transactions on information theory, Vol. 56, No. 1, 2010, pp. 520-544.
[14]
J. N. Laska, S. Kirolos, M. F. Duarte, T. S. Ragheb, R. G. Baraniuk, Y. Massoud, Theory and implementation of an analog-to-information converter using random demodulation, IEEE International Symposium on Circuits and Systems, 2007, pp. 1959-1962.
[15]
J. Romberg. Compressive sensing by random convolution. 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2007, pp. 137-140.
[16]
J. A. Tropp, M. B. Wakin, M. F. Duarte, D. Baron, R. G. Baraniuk, Random filters for compressive sampling and reconstruction, IEEE International Conference on Acoustics, Speech and Signal Processing, 2006, pp. III.
[17]
D. Takhar, J. N. Laska, M. Wakin, M. F. Duarte, D. Baron, S. Sarvotham, K. F. Kelly, R. G. Baraniuk, A new compressive imaging camera architecture using optical-domain compression, Computational Imaging, 2006.
[18]
G. L. Fudge, R. E. Bland, M. A. Chivers, S. Ravindran, J. Haupt, P. E. Pace, A Nyquist folding analog-to-information receiver, 42nd Asilomar Conference on Signals, Systems and Computers, 2008, pp. 541-545.
- Intercept of frequency agility signal using coding Nyquist folding receiver
Recommendations
Time Domain Error Analysis for Pulse Signal Based on Nyquist Folding Receiver
ICGSP '17: Proceedings of the 1st International Conference on Graphics and Signal ProcessingNyquist folding receiver (NYFR) is a novel kind of analog-to-information architecture and it uses non-uniform sampling to realize the wideband receiving. In this paper, the time domain error of the pulse signal intercepted by the NYFR is analyzed. ...
Fundamentals of coding for broadcast OFDM
ASILOMAR '95: Proceedings of the 29th Asilomar Conference on Signals, Systems and Computers (2-Volume Set)The same information is often broadcast to many receivers over different frequency selective channels. Digital audio signals and digital video signals are commonly distributed by such broadcasts. A coded modulation technique for orthogonal frequency ...
Characteristics Analysis and Frequency Estimation of Multi-Tone Signals Based on NYFR
ICGSP '17: Proceedings of the 1st International Conference on Graphics and Signal ProcessingThis paper firstly introduces an efficient analogy-to-information (A2I) architecture called Nyquist folding receiver (NYFR) that folds the broadband RF inputs by subsampling with sinusoid phase modulation. We then deduce the expression of each process ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
World Scientific and Engineering Academy and Society (WSEAS)
Stevens Point, Wisconsin, United States
Publication History
Published: 01 April 2011
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Jan 2025