Abstract: Radar target recognition technology is a means to identify remote targets by using radar and computer, and has been widely used in modern radar field. However, the existing recognition methods need to be retrained for new data, which is not conducive to the realization of model speed and online function. Based on this, this paper proposes a broad convolution neural network (BCNN), since the model has the "width" network structure, which can use newly generated additional features, and improve the recognition performance of BCNN model, BCNN model is also able to use new training data to update themselves, thus has the incremental learning ability. Experimental results show that this method can better extract the features of the data, and the recognition accuracy is more than 8% higher than that of conventional CNN, the model can update itself to include the newly emerging radar data, so it has stronger practicability and robustness.