Under the urban forest or indoor environments, the received Global Navigation Satellite System (GNSS) signal may be affected by the multipath effects and be sheltered from the buildings. These influences will reduce the strength of the received signal. Furthermore, the strong signals, called interferences which are natural or artificial Electro-Magnetic Interferences (EMIs), can interfere with GPS receivers while they are within the radio frequency or light of sight. The interference might result in degraded navigation accuracy or complete loss of receiver tracking. In recent years, researches on the weak GNSS signal acquisition have attracted a lot of attentions to provide an accurate position service for indoor environment. A solution is represented by the Time-Frequency (TF) analysis which is capable of detecting and subsequently removing a great variety of disturbing signals. Current TF methods require lower computational loads and may be suitable for real-time applications, but their spectrogram has poor TF localization properties. This paper therefore uses a TF analysis method based on the Fourier sine spectrum to obtain a spectrogram with small error. It could provide an effective tool for detecting the interference of the received GPS signals by means of the two dimensional time-frequency analysis. As a part of this paper, this paper also uses the proposed TF analysis to be an identification tool. It can confirm whether a signal exists while the estimated SNR is close to the predetermined threshold. Consequently, the analytical background of the time-frequency analysis is introduced. Several simulations and experiments are conducted to validate the effectiveness of the proposed time-frequency spectrogram method. The results show that the time-frequency analysis is effective to detect and locate interference sources from the proposed time-frequency spectrum as well.