Data Processing Architecture for Target Tracking

In this section, we first define the process and observation models for target tracking. Then the foundations of the distributed data fusion architecture are presented. 

The target process is a four dimensional vector that consists of the two dimensional position of the target, ( , rj), and the velocity of the target, (, )), at each of these dimensions. The target process state vector is defined by 

Sensors can only observe the first two dimensions of the process. The velocity of the target is not observable by the sensors. Furthermore, sensors collect range and bearing data, but they cannot observe the coordinates of the target directly. Because sensors observe the target state 

The measured range and bearing are defined with respect to the true range r and bearing 9 as 

The target mean state observed after the unbiased polar-to-Cartesian conversion is given by 

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