Broadband detection of signals with unknown spectra

The problem of detection of a broadband wide sense stationary Gaussian signal of unknown power spectral density in white Gaussian noise is addressed. By modeling the signal in noise as an autoregressive process a generalized likelihood ratio test is formulated for the parameters of the autoregressive process. It is shown that the proposed detector outperforms the conventional energy detector. The gain in performance is greatest when the autoregressive model order is small.