Prof. Danilo Orlando (Universita degli Studi Niccolo’ Cusano, Roma, Italy)
Abstract: Nowadays, radar systems are bound to operate in spectrally Nowadays, radar systems are bound to operate in spectrally crowded environments where multiple electromagnetic intentional and/or unintentional sources might interfere with the signal of interest. Many approaches can be pursued to overcome this drawback as, for instance, the real-time adaptation of the transmitted wave forms to the specific scenario after having sensed it or the design of suitable detection architectures that incorporate signal-processing-related Electronic Counter-Counter Measures against interfering signals. In this talk, we focus on the latter solution and present some recent advances in this context. Specifically, we start with the design of suitable estimation procedures for the interference covariance matrix capable of accounting for the presence of noise-like jammers in addition to clutter and thermal noise. Then, we consider the problem of contrasting structured interference (deceptive jammers) and describe effective solutions based upon compressive sensing techniques which allow for signal classification. Finally, we exploit such techniques to come up with selective detection architectures, whose probability of detection rapidly decreases when the target signature moves away from the nominal pointing direction. Thus, they can work in target rich environments at the price of a performance degradation for perfectly matched signals where multiple electromagnetic intentional and/or unintentional sources might interfere with the signal of interest. Many approaches can be pursued to overcome this drawback as, for instance, the real-time adaptation of the transmitted wave forms to the specific scenario after having sensed it or the design of suitable detection architectures that incorporate signal-processing-related Electronic Counter-Counter Measures against interfering signals. In this talk, we focus on the latter solution and present some recent advances in this context. Specifically, we start with the design of suitable estimation procedures for the interference covariance matrix capable of accounting for the presence of noise-like jammers in addition to clutter and thermal noise. Then, we consider the problem of contrasting structured interference (deceptive jammers) and describe effective solutions based upon compressive sensing techniques which allow for signal classification. Finally, we exploit such techniques to come up with selective detection architectures, whose probability of detection rapidly decreases when the target signature moves away from the nominal pointing direction. Thus, they can work in target rich environments at the price of a performance degradation for perfectly matched signals.