Aiming at the problem that the traditional target detection algorithm has poor detection effect on small vehicle targets in aerial images, a vehicle detection algorithm based on improved Faster R-CNN is proposed.Based on the original Faster R-CNN network, this method combines FPN as the basic network model—FFRCNN, ResNet-50 is applied instead of original VGG-16 as the main backbone network for multi-feature fusion, and Focal Loss function is used to correct the imbalance between positive and negative samples.On the basis of improving the network, atrous convolution is used to fuse the feature information of multi-scale space, which can improve the receptive field of the network and better collect the context information of the image.The experimental results show that the average accuracy of the improved detection algorithm reaches 93.8%, which is 19.2% higher than that of the original FFRCNN network and has better robustness.