Contact clustering and fusion for preprocessing multistatic active sonar data

This paper presents results of a clustering-based preprocessing step for multistatic tracking, evaluated on the PACsim dataset, a simulated multistatic active sonar dataset. The clustering step uses a flexible likelihood-based similarity calculation which allows for the incorporation of any available features. In this work, we present results using target strength (estimated from signal-to-noise ratio) and Doppler measurements. Results show that this approach performs well on dim targets in high clutter environments.