TY - GEN

T1 - Separation of chirp scattered returns from a mixture of sinusoidal tones in noise

AU - Farshchian, Masoud

AU - Selesnick, Ivan

PY - 2016/11/15

Y1 - 2016/11/15

N2 - We consider the problem of source separation of a signal whose elements consist of chirp scattered returns and sinusoidal tones overlapping in time and frequency. Due to the application, both signals are assumed to be highly non-stationary with their parameters rapidly changing. Such a mixture may occur when a device with a single antenna is spectrally constrained while simultaneously communicating information and sensing the environment. Another application is to mitigate interference between two devices which must share the spectrum. We consider a formulation where the chirp scattered returns are modeled as a convolution and the sinusoidal tones are modeled as sparse in the overcomplete inverse discrete Fourier domain. The objective function which is a combination of basis pursuit denoising and deconvolution is formulated with a/i-norm regularizer for each signal. A fast transform based iterative algorithm to obtain the solution is presented and the major steps for deriving the solution are outlined. Simulation results are provided where the non-linear separation algorithm yields a significant improvement in signal reconstruction relative to the standard matched-filter.

AB - We consider the problem of source separation of a signal whose elements consist of chirp scattered returns and sinusoidal tones overlapping in time and frequency. Due to the application, both signals are assumed to be highly non-stationary with their parameters rapidly changing. Such a mixture may occur when a device with a single antenna is spectrally constrained while simultaneously communicating information and sensing the environment. Another application is to mitigate interference between two devices which must share the spectrum. We consider a formulation where the chirp scattered returns are modeled as a convolution and the sinusoidal tones are modeled as sparse in the overcomplete inverse discrete Fourier domain. The objective function which is a combination of basis pursuit denoising and deconvolution is formulated with a/i-norm regularizer for each signal. A fast transform based iterative algorithm to obtain the solution is presented and the major steps for deriving the solution are outlined. Simulation results are provided where the non-linear separation algorithm yields a significant improvement in signal reconstruction relative to the standard matched-filter.

UR - http://www.scopus.com/inward/record.url?scp=85002648976&partnerID=8YFLogxK

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U2 - 10.1109/CoSeRa.2016.7745721

DO - 10.1109/CoSeRa.2016.7745721

M3 - Conference contribution

AN - SCOPUS:85002648976

T3 - 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016

SP - 163

EP - 167

BT - 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016

Y2 - 19 September 2016 through 23 September 2016

ER -