Abstract: ‍ ‍The slowly varying spoofing interference signal is consistent with the real signal of the global navigation satellite system （GNSS） in the early stage of interference， which has strong concealment and is difficult to detect effectively. The common slowly varying spoofing interference detection method usually uses the Kalman filter innovation sequence as the detection amount， and it detects the slowly varying spoofing interference based on the chi-square test. However， these methods have the problems of long detection time and low detection performance. Aiming at the problems， a spoofing detection algorithm for slowly varying spoofing interference based on SPRT was proposed， which used the detection amount of the innovation sequence as the SPRT sample to calculate the test statistic. The spoofing detection algorithm could identify the spoofed satellite while detecting the slowly varying spoofing interference. Simultaneously， using Bayes parameter estimation theory， an adaptive SPRT algorithm was proposed， which adaptively compensated the test statistics， speeded up the detection speed of the algorithm， and could further improve the detection performance of the algorithm by adjusting the risk parameters. The simulation results show that， compared with the traditional method， the algorithm in this paper has a shorter detection time and high detection performance for slowly varying spoofing interference， and it can achieve better detection performance when multiple satellites are spoofed.