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We consider a general spectral coexistence scenario, wherein the channels andtransmit signals of both radar and communications systems are unknown at thereceiver. In this \textit{dual-blind deconvolution} (DBD) problem, a commonreceiver admits the multi-carrier wireless communications signal that isoverlaid with the radar signal reflected-off multiple targets. When the radarreceiver is not collocated with the transmitter, such as in passive ormultistatic radars, the transmitted signal is also unknown apart from thetarget parameters. Similarly, apart from the transmitted messages, thecommunications channel may also be unknown in dynamic environments such asvehicular networks. As a result, the estimation of unknown target andcommunications parameters in a DBD scenario is highly challenging. In thiswork, we exploit the sparsity of the channel to solve DBD by casting it as anatomic norm minimization problem. Our theoretical analyses and numericalexperiments demonstrate perfect recovery of continuous-valued range-time andDoppler velocities of multiple targets as well as delay-Doppler communicationschannel parameters using uniformly-spaced time samples in the dual-blindreceiver.

Joint Radar-Communications Processing from a Dual-Blind Deconvolution Perspective