In many modern GPR systems, it is desired to detect the presence of targets in the interference which includes clutter and noise. Detection of water leaks using GPR has been aimed in this work. Pipe and soil are known as the clutter of data in this scenario. Various signal processing techniques like multivariate subspace-based algorithms are proposed to effectively suppress the clutter and increase the signal to interference ratio. Combining Independent Component Analysis (ICA) and Principal Component Analysis (PCA) as a unique algorithm has demonstrated the ability to eliminate the GPR clutter and extract the target signal.