A Novel Ghost Elimination In Passive Radar Systems
In this paper, a novel algorithm is proposed for the detection and localization problem of multiple targets. Angle-of-arrival(AoA) and time-of-arrival(ToA) measurements collected by passive radars are associated effectively. Constructing clusters with using these measurements and calculating scores for each cluster enable to solve ghost target problem faced in bearing association. AoA measurements and hyperbola intersections founded by using ToA measurements are utilized in score assignment. Moreover, entropy is used to differentiate real targets from ghost targets more efficiently. Target position estimation is performed using maximum likelihood estimation for clusters having the highest scores. In the test stage, scenarios are designed for a different number of targets and different noise levels.
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