4.3 Sensor Fusion

Sensor and data fusion as a research discipline in its own right, emerged largely as a result of various Defence organisations attempting to formalise procedures for integrating information from disparate sources. The object of the exercise was to determine battlefield situation and assess threat on the basis of data coming in from numerous different channels. A sensor in this context is simply a provider of data and may be a true sensor in the physical sense like a microwave antenna or even a human intermediary. The philosophy of data fusion was quickly recognised to have broader application; initially in the fields of meteorology and traffic management, but later in the medical field and in non-destructive testing (NDT).

Thus, the whole purpose of sensor fusion as a discipline is to integrate data from a multitude of sensors with the objective of making a more robust and confident decision than is possible with any one sensor alone. There are numerous reasons why multi-sensor systems are desirable, following ^[2]:

• Higher signal-to-noise ratio. (Sensor fusion can be as simple as averaging the results from several identical sensors. In practice, ergodicity ^{[ ]} helps here by allowing averages over sensors to be replaced by averaging over time.)

• Robustness and reliability. Enough information may be available to form a decision even if a subset of the sensors fail. Note that in order to have fault tolerance, it is necessary to design in redundancy and thus increase the dimension...