Staggered SAR can simultaneously get the ability of high azimuth resolution and wide range swath. However, it also causes pairs of azimuth ambiguities on imaging result because of its non-uniform sampling mode. In this paper, we proposed an innovative ambiguity removal method based on deep learning algorithm with a deep fully convolution and residual neural network. Traditional techniques are constrained in the steps of signal recovering and resampling thus only work at high over-sampling rate. Different from them, the deep learning method doesn't need to record the lost pulses for signal reconstruction and performances well at low over-sampling rate. The simulation results verify the effectiveness of our method and it behaves better than other traditional method.