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In this contribution we present a sensor data fusing concept utilizing particle filters. The investigation aims at the development of a robust and easy to extend approach, capable of combining the information of different sensors. We use the particle filters characteristics and introduce weighting functions that are multiplied during the measurement update stage of the particle filter implementation. The concept is demonstrated in a vehicle detection system that conjoins symmetry detection, tail lamp detection and radar measurements in night vision applications.