Compressed Localization and Spectrum Sensing for Cognitive Radio and Distributed Radio Surveillance - CLASS

This DFG-project aims at exploiting the advantages in terms of sampling requirements brought along by the compressed sensing framework to attain highly spectrally efficient cyclostationary time-difference-of-arrival (TDOA) based transmitter localization. To achieve this goal, the inherent sparsity of the cyclic autocorrelation function (CAF) as well as other properties of the CAF will be taken into account when designing new methods for its recovery from incomplete measurements.


For further information please contact Andreas Bollig.