Many studies have been done so far based on the detection theory for target detection in active radars, but not for passive radars. Owing to some substantial differences, detection methods used in active radars do not...
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Many studies have been done so far based on the detection theory for target detection in active radars, but not for passive radars. Owing to some substantial differences, detection methods used in active radars do not lead to accurate results if applied to passive radars. So, in the current study, cancellation, detection and target parameter extraction are investigated for passive radar based on the detection theory. To do this, the passive radar hypothesis test is written in the form of a multiple composite test. Unknown parameters are estimated using maximum likelihood (ML) criterion for the achievement of generalised likelihood ratio test detection statistic and elimination of direct path and clutter that contain nuisance parameters. The required threshold is set so that the false alarm probability in each cell and each step would become a constant value. Also, since this method requires heavy computations, a method for the reduction of computational complexity is proposed. Finally, various detection methods in passive radars are compared using simulation to show the effectiveness of the suggested method.
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