Interference-resistant detection based on time-frequency subspaces

The difficulty of modeling interference is one of the main problems in constructing an efficient interference-resistant detector. We present a new detector which exploits the signal correlation structure to account for interference. In order to make a decision between two composite hypotheses, our detector uses the generalized likelihood ratio test. Preliminary results suggest that the resulting detection scheme achieves high performance in presence of strong interference.