Lightweight feature fusion network design for local feature recognition of non-cooperative target

The Non-cooperative Detection Network(NCDN) model is a kind of local feature detection network based on lightweight convolution neural network. In SSD model, the feature fusion strategy was introduced to meet the detection requirements at different distances, and the robustness of the model to the reduction of local feature resolution caused by image scale transformation was improved; the number of convolution channels in mobilenetv2 was compressed with different compression ratios to obtain lightweight feature extraction network; local feature labeling and training of speed data were set to verify the applicable distance range of NCDN. The experimental results show that the mAP of the model can reach 0.90 within 45 m, and the accuracy loss of the model is only 5% after saving 75% of the calculation amount in channel compression. It meets the requirements of on orbit detection accuracy and calculation amount.