摘要 : The radar network employs multisource data-level fusion to discriminate and suppress deceptive false target interference based on the “spatial colocation” differences between genuine and false targets, which severely threaten actu... 展开 The radar network employs multisource data-level fusion to discriminate and suppress deceptive false target interference based on the “spatial colocation” differences between genuine and false targets, which severely threaten actual targets. We propose a multisource collaborative spatial decoy target deception method to enhance the jamming and counteraction capabilities of jammers against the radar network. This method utilizes prior information about the quantity and positions of our jamming devices and the enemy radar network. It constructs a multisource collaborative spatial decoy target deception model and employs optimization to determine the jammer positions, decoy target locations, and jamming parameters. Each jammer adjusts its transmission delays and modulates the jamming signal phase and amplitude to achieve highly flexible, real-time, spatially colocated deception in the spatial, temporal, and Doppler domains. Multiple jammers collaborate to create realistic, positively correlated tracks within the radar network, effectively providing cover for our target's penetration. Formula derivations and simulation experiments confirm the effectiveness of this multisource collaborative spatial decoy target deception, significantly enhancing the disruption capabilities of airborne clusters against the radar network. 收起