Spectrum sensing for radar communications with unknown noise variance and time-variant channel

In this paper, a new spectrum sensing framework is proposed for radar communications, which recovers other informative states associated with realistic radar environments, e.g. fading channel gains and unknown noise variance, when detecting the occupancy of primary-band. We firstly formulate a dynamic state-space model by full considering the unknown noise variance and time-variant flat fading channel. On this basis, a novel spectrum sensing scheme, relying on maximum a posteriori probability criterion and marginal particle filtering technology, is designed to estimate the state of primary user, time-variant fading channel gain and noise variance jointly. Experimental simulations show that the proposed method improves the sensing performance significantly and estimate the fading channel gain and noise variance accurately.