Maximum Information Fusion of Passive and Active Radars for Air Surveillance

Modern passive radar systems seem promising as cost-effective gap fillers of active radar coverage and also as covert early warning sensors. Integration of passive systems into already operational active radar networks is therefore of great interest to military and civilian air surveillance. We here propose a maximum information fusion approach specifically for solving this issue demonstrating a data association, data fusion and tracking method for bistatic passive radar and monostatic active radar data in air surveillance. Conventionally, separate bistatic and Cartesian trackers in two stages are proposed to provide a combined air picture. Such approaches effectively avoid false plots of the passive radar systems being tracked. However, these approaches also filter out potentially valid plots, which could have proven valuable if fused with active radar plots directly. This is especially of relevance in challenging terrain such as alpine valleys with scarce transmitters of opportunity and active radar clutter. We test our approach using real world passive and active radar data. While the tracking performance of our im-plementation is markedly inferior to existing commercial passive radar systems, our prototypical implementation demonstrates the feasibility and potential of the new approach for passive and active radar data fusion at the plot level.