Biblio

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2018-05-23
S. Chen, J. Weimer, M. Rickels, A. Peleckis, I. Lee.  Submitted.  Physiology-Invariant Meal Detection for Type 1 Diabetes. Diabetes Technology and Therapeutics", year 201.

online first

2017-02-21
C. Liu, F. Xi, S. Chen, Z. Liu.  2015.  "Anti-jamming target detection of pulsed-type radars in QuadCS domain". 2015 IEEE International Conference on Digital Signal Processing (DSP). :75-79.

Quadrature compressive sampling (QuadCS) is a newly introduced sub-Nyquist sampling for acquiring inphase and quadrature components of radio-frequency signals. This paper develops a target detection scheme of pulsed-type radars in the presence of digital radio frequency memory (DRFM) repeat jammers with the radar echoes sampled by the QuadCS system. For diversifying pulses, the proposed scheme first separates the target echoes from the DRFM repeat jammers using CS recovery algorithms, and then removes the jammers to perform the target detection. Because of the separation processing, the jammer leakage through range sidelobe variation of the classical match-filter processing will not appear. Simulation results confirm our findings. The proposed scheme with the data at one eighth the Nyquist rate outperforms the classic processing with Nyquist samples in the presence of DRFM repeat jammers.

S. Chen, F. Xi, Z. Liu, B. Bao.  2015.  "Quadrature compressive sampling of multiband radar signals at sub-Landau rate". 2015 IEEE International Conference on Digital Signal Processing (DSP). :234-238.

Sampling multiband radar signals is an essential issue of multiband/multifunction radar. This paper proposes a multiband quadrature compressive sampling (MQCS) system to perform the sampling at sub-Landau rate. The MQCS system randomly projects the multiband signal into a compressive multiband one by modulating each subband signal with a low-pass signal and then samples the compressive multiband signal at Landau-rate with output of compressive measurements. The compressive inphase and quadrature (I/Q) components of each subband are extracted from the compressive measurements respectively and are exploited to recover the baseband I/Q components. As effective bandwidth of the compressive multiband signal is much less than that of the received multiband one, the sampling rate is much less than Landau rate of the received signal. Simulation results validate that the proposed MQCS system can effectively acquire and reconstruct the baseband I/Q components of the multiband signals.

2018-05-23
I. Lee, O. Sokolsky, S. Chen, John Hatcliff, E. Jee, B. Kim, A. King, M. Fortino-Mullen, S. Park, A. Roederer et al..  2012.  Challenges and Research Directions in Medical Cyber-Physical Systems. Proceedings of the {IEEE} (special issue on Cyber-Physical Systems). 100:75–90.