TY - GEN
T1 - Time-Frequency Separation of Matched-Waveform Signatures of Coexisting Multimodal Systems
AU - Gattani, Vineet Sunil
AU - Kota, John S.
AU - Papandreou-Suppappola, Antonia
N1 - Funding Information:
This work was supported in part by AFOSR Grant FA9550-17-1-0100
Publisher Copyright:
© 2018 IEEE.
PY - 2019/2/19
Y1 - 2019/2/19
N2 - As the demand for wireless systems increases exponentially, it has become necessary for different wireless modalities, like radar and communications systems, to share the available bandwidth. One approach to realize coexistence successfully is for each system to adopt a transmit waveform with a unique nonlinear time-varying phase function. At the receiver of the system of interest, the waveform received for processing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the presence of the waveforms that are matched to the other coexisting systems. This paper uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched to the system. Specifically, the IF is estimated using the synchrosqueezing transform, a highly localized time-frequency representation that also enables reconstruction of individual waveform components. As the IF estimate is biased, modified versions of the transform are investigated to obtain estimators that are both unbiased and also matched to the unique nonlinear phase function of a given waveform. Simulations using transmit waveforms of coexisting wireless systems are provided to demonstrate the performance of the proposed approach using both biased and unbiased IF estimators.
AB - As the demand for wireless systems increases exponentially, it has become necessary for different wireless modalities, like radar and communications systems, to share the available bandwidth. One approach to realize coexistence successfully is for each system to adopt a transmit waveform with a unique nonlinear time-varying phase function. At the receiver of the system of interest, the waveform received for processing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the presence of the waveforms that are matched to the other coexisting systems. This paper uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched to the system. Specifically, the IF is estimated using the synchrosqueezing transform, a highly localized time-frequency representation that also enables reconstruction of individual waveform components. As the IF estimate is biased, modified versions of the transform are investigated to obtain estimators that are both unbiased and also matched to the unique nonlinear phase function of a given waveform. Simulations using transmit waveforms of coexisting wireless systems are provided to demonstrate the performance of the proposed approach using both biased and unbiased IF estimators.
KW - Coexisting systems
KW - multimodal sensing
KW - ridge extraction
KW - synchrosqueezing
KW - time-frequency
UR - http://www.scopus.com/inward/record.url?scp=85062965525&partnerID=8YFLogxK
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U2 - 10.1109/ACSSC.2018.8645255
DO - 10.1109/ACSSC.2018.8645255
M3 - Conference contribution
AN - SCOPUS:85062965525
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 2086
EP - 2090
BT - Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Y2 - 28 October 2018 through 31 October 2018
ER -