The Fetal Heart Rate (FHR) periodic monitoring is essential part during pregnancy. The gold standard in fetal examination is the ultrasound but it is not suggested for long-term monitoring due to the cost of the instrument, the need of an expert to make the implementation and the suspicion of being noxious for the fetus in long-term use. On the contrary, auscultation is a noninvasive low cost technique for the heart sound examination. However, Fetal Phonocardiogram (fPCG) signals are correlated with high background noise due to the maternal breathing and heart sounds, fetal movement, etc. The aim of this study is to develop an automatic analysis technique to identify the location of the FHSs in fPCGs signals and calculate the FHR . In this paper two denoising methods are proposed and compared in real and simulated fPCGs signals. The PhysioBank simulated fPCG database was used for testing the methods in simulated signals along with 3 real fPCGs signals from a four-channel fPCG sensor for testing in real conditions.The signals were analysed in the Wavelet domain and then two methods were proposed for the detection of the FHSs. The first approach combines the Wavelet Transform with the Fractal Dimension analysis (WT-FD) while the second approach combines the Wavelet Transform with Simplicity Filtering (WT-S), which is computed by the eigenvalue spectrum method. Preliminary results show that both methods have similar performance with the WT-FD presets 81% precision, 89% recall and WT-S 78% and 84% respectively in simulated signals from -4.4 to -24.4dB, while the WT-S method is more unstable in relation to the type of noise than the WT-FD. In real fPCGs signals a preprocessing filter with the combination of the four different channels is a necessary additional step to remove the sounds of the mother to reveal and study the FHS.