Mobile radiation sensor networks integrated with global positioning system coordinates provide an attractive option for the task of dynamically monitoring a region's background radiation and detecting the illicit movement of radioactive materials. Both statistical and probabilistic approaches have been developed for stationary sensor networks to estimate source parameters. In this paper, a pre-filter framework for mobile sensor networks is presented that estimates multiple sources' positions and intensity without prior knowledge about the sources. The pre-filter framework contains a segmentation algorithm, a clustering algorithm and a maximum likelihood estimation algorithm. With adequate number of measurements, the pre-filter framework estimates source parameters in high accuracy. This offers an efficient alternative to traditional approaches where the multi-source problems are difficult to solve.