Satellite navigation receiver has two different underlying architectures, including scalar tracking and vector tracking. The vector tracking receiver processes all the channels using a center navigation filter. This architecture could utilize the sharing information for improving the receiver performance. However, the channels will affect each other in this architecture. Channels with signal blockage or weaker signal will affect the navigation filter operation, and it is necessary for carrying out channel status monitoring. In this paper, a long short term memory-recurrent neural networks (LSTM-RNN) is proposed and applied in the channel status monitoring. The innovative sequence of the center navigation filter is employed as the input vector of the LSTM-RNN. Simulation results show that the proposed method could detect faults effectively and ensure the positioning accuracy of vector tracking receiver.