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Simultaneous registration and trading has advantages over other track registration techniques because it is capable of responding to changes in registration errors. The track registration problem is presented for a network of two geographically distributed radars with unknown measurement, biases that are fixed or slowly varying. The extended Kalman filter that receives unregistered and cluttered plots from the radars and outputs registered trades, is used to carry out centralized simultaneous registration and trading. A multisensor probabilistic data association filter (PDAF) that combines locally gated plots from the radars is developed to enable the system operation under clutter. The algorithm satisfies a number of important registration design criteria.