Structure-aware Bayesian compressive sensing for frequency-hopping spectrum estimation

Shengheng Liu; Yimin D. Zhang; Tao Shan; Si Qin; Moeness G. Amin

doi:10.1117/12.2228339

4 May 2016 Structure-aware Bayesian compressive sensing for frequency-hopping spectrum estimation

Shengheng Liu, Yimin D. Zhang, Tao Shan, Si Qin, Moeness G. Amin

Proceedings Volume 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics; 98570N (2016) https://doi.org/10.1117/12.2228339
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

Abstract

Frequency-hopping (FH) is one of the commonly used spread spectrum techniques that finds wide applications in communications and radar systems due to its capability of low probability of intercept, reduced interference, and desirable ambiguity property. In this paper, we consider the blind estimation of the instantaneous FH spectrum without the knowledge of hopping patterns. The FH signals are analyzed in the joint time-frequency domain, where FH signals manifest themselves as sparse entries, thus inviting compressive sensing and sparse reconstruction techniques for FH spectrum estimation. In particular, the signals' piecewise-constant frequency characteristics are exploited in the reconstruction of sparse quadratic time-frequency representations. The Bayesian compressive sensing methods are applied to provide high-resolution frequency estimation. The FH spectrum characteristics are used in the design of signal-dependent kernel within the framework of structure-aware sparse reconstruction.

Citation Download Citation

Shengheng Liu, Yimin D. Zhang, Tao Shan, Si Qin, and Moeness G. Amin "Structure-aware Bayesian compressive sensing for frequency-hopping spectrum estimation", Proc. SPIE 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics, 98570N (4 May 2016); https://doi.org/10.1117/12.2228339

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