Model-Based Data Fusion

In an air defence weapon system, the radars are placed optimally considering attack and defence profiles. These radars can be of different accuracies with possibility of tracking the target for interception. Depending on the threat and geometry of defence units, the location of target relative to the radars can be different. Therefore, the accuracy of target tracks from the radars is different during the mid-course and homing guidance. Hence, it is imperative to improve tracking accuracy in order to reduce the miss distance. The fusion of target state vectors can improve the tracking accuracy.

The model-based data fusion technique, which is state vector fusion in essence, has been developed by DRDO for accuracy improvement in x, y, z components, guarding against data loss from a sensor, increasing the number of measurements during homing, and bump less transfer within the sensor set. The technique can be used in real time to provide data to the guidance system with better accuracy and reliability.

Salient Features

• Synchronized measurements not required
• Measurement extrapolation avoided
• Centralised fusion of distributed sources possible