Method and system for multi-sensor data fusion using a modified dempster-shafer theory

A multi-sensor data fusion system and method provide an additive fusion technique including a modified belief function (algorithm) to adaptively weight the contributions from a plurality of sensors in the system and to produce multiple reliability terms including reliability terms associated with noise for low SNR situations. During a predetermined tracking period, data is received from each individual sensor in the system and a predetermined algorithm is performed to generate sensor reliability functions for each sensor based on each sensor SNR using at least one additional reliability factor associated with noise. Each sensor reliability function may be individually weighted based on the SNR for each sensor and other factors. Additive calculations are performed on the reliability functions to produce at least one system reliability function which provides a confidence level for the multi-sensor system relating to the correct classification (recognition) of desired objects (e.g., targets and decoys).