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Channel probability ensemble update for multiplatform radar systems

Cognitive radar (CR) is a recently proposed concept that depicts the radar channel in a probabilistic manner. In a multiplatform or networked radar system, some parameters or dimensions of interest are visible (i.e., resolvable) to one radar and not to others depending on the geometry of the scenario. For a radar with new measurements, Bayesian methods to update the cell ensemble probabilities in the non-visible parameters are needed. Here, we show how the overall probabilistic understanding of the channel can be updated despite the fact that some cells are non-visible or “ambiguous”. Unfortunately, the number of calculations needed to accomplish a full update is exponentially related to the number of cells. As such, we also introduce a technique that reduces the calculations immensely. Finally, we apply both update techniques to a two-platform radar system trying to form a two-dimensional probability ensemble of the channel.