Unmanned aerial vehicle cluster target long-time robust tracking method under low-altitude airspace complex environment

Abstract

The application discloses a kind of low air space complex environment under unmanned aerial vehicle cluster target long-time robust tracking method, comprising: by the target detection model of pre-training to the unmanned aerial vehicle target is detected and is combined with environmental state information dynamic optimization;The detection result after optimization is parallelly input light graph convolution network and bidirectional LSTM module, respectively extract the spatial interaction feature and time sequence dynamic feature of target predicted position;Two kinds of features are fused using spatial-time sequence attention mechanism, to obtain more accurate predicted position information;Based on the confidence score of target detection frame, the predicted position of target and the actual detection result of target are two-stage data association.The method effectively improves the tracking accuracy and robustness of unmanned aerial vehicle cluster target in complex dynamic environment, especially in target occlusion, dense formation and background interference scene has strong adaptability.

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