Adaptive Detection of a Subspace Signal in Signal-Dependent Interference

This paper deals with the problem of adaptive detection of subspace signals embedded in thermal noise and clutter that depends on the transmitted signal. To this end, at the design stage, we assume that the signal-dependent (SD) clutter shares the same subspace as the target signals. As customary, a set of secondary data, free of signal components, is also assumed available. Two adaptive detectors, referred to as the SD Rao and SD Wald, are proposed by resorting to the Rao test and Wald test design criteria. Unlike the classical Rao and Wald tests, which are derived by dividing the complex parameter into the real and imaginary parts, the proposed detectors treat the complex parameter as a single quantity to reduce the computational burden. Moreover, we derive the theoretical false alarm probabilities and detection probabilities and show that both the two proposed detectors exhibit the constant false alarm rate property. Numerical results show that the proposed detectors achieve a detection performance improvement over the conventional multidimensional detectors.