Adaptive detection based on gradient test and Durbin test in spectrally symmetric interference

In this paper, we consider the problem of detecting a signal in ground clutter dominated environments with a symmetrically structured power spectral density. We take advantage of interference’s spectrum symmetry to develop decision schemes. The gradient test, Durbin test and their two-step (2S) variants are deduced. The 2S-gradient test and the 2S-Durbin test coincide with the 2S generalized likelihood ratio test, and the Durbin test coincide with the Rao test for the same detection problem, while the gradient test is a new detector. Numerical results, based on simulated and real data, show that the gradient test can perform better than the existing ones in sample-starved scenarios, and the detectors exploiting the interference spectrum symmetry outperform traditional detectors without exploiting the interference spectral symmetry.