基于层级交叉注意力网络的无人机被动感知方法OA

To address weak echo submersion and multipath interference in digital terrestrial multimedia broadcast(DTMB)external illuminator,a UAV passive sensing method based on hierarchical cross-attention network(HCANet)was proposed.A dual-branch architecture was constructed to extract temporal dependencies via time-domain multi-scale convolution and micro-Doppler features via frequency-domain amplitude-phase joint encoding.Hierarchical cross-attention modules were utilized to adaptively align and fuse time-frequency features in the feature space.Experimental results show that the method maintaines robustness within-10 to 10 dB signal-to-noise ratios.The detection accuracy un-der 10 dB additive white Gaussian noise,Rician,and Rayleigh channels reaches 95.75%,99.50%,and 71.25%,respec-tively,and the accuracy of measured data in complex urban environments reaches 99.65%.These results validate the ef-fectiveness in low signal-to-noise ratio and strong-scattering environments.