A system to determine a most likely position of an object, said system comprising: a plurality of sensors each providing an estimated position of the object; and a data processor for: determining an associated sensor probability distribution for each sensor based on the estimated position of the object provided by the sensor and performance characteristics of the sensor, wherein the performance characteristics of the sensor are either accessed by the data processor from a database or provided to the data processor by the sensor, further wherein the performance characteristics of the sensor include at least one of accuracy, reliability, effect of environmental conditions, and degradation with age; segmenting the associated sensor probability distribution for each sensor into sub-ranges, wherein every sub-range is represented by an uncertainty boundary segment; for each sub-range,_assigning a probability measure reflective of the reliability of each sensor to sense the position of the object; using statistical simulation to manipulate the probability measures associated with each sub-range of each sensor to generate a value indicative of the most likely position of the object and an associated probability distribution for the most likely position of the object; applying a conjunctive fusion method to_the estimated position of the object from each of the plurality of sensors and the associated sensor probability distributions to identify an intersection region of the sub-ranges with the most likely probability of defining the position of the object. a plurality of sensors each providing an estimated position of the object; and a data processor for: determining an associated sensor probability distribution for each sensor based on the estimated position of the object provided by the sensor and performance characteristics of the sensor, wherein the performance characteristics of the sensor are either accessed by the data processor from a database or provided to the data processor by the sensor, further wherein the performance characteristics of the sensor include at least one of accuracy, reliability, effect of environmental conditions, and degradation with age; segmenting the associated sensor probability distribution for each sensor into sub-ranges, wherein every sub-range is represented by an uncertainty boundary segment; for each sub-range,_assigning a probability measure reflective of the reliability of each sensor to sense the position of the object; using statistical simulation to manipulate the probability measures associated with each sub-range of each sensor to generate a value indicative of the most likely position of the object and an associated probability distribution for the most likely position of the object; applying a conjunctive fusion method to_the estimated position of the object from each of the plurality of sensors and the associated sensor probability distributions to identify an intersection region of the sub-ranges with the most likely probability of defining the position of the object. determining an associated sensor probability distribution for each sensor based on the estimated position of the object provided by the sensor and performance characteristics of the sensor, wherein the performance characteristics of the sensor are either accessed by the data processor from a database or provided to the data processor by the sensor, further wherein the performance characteristics of the sensor include at least one of accuracy, reliability, effect of environmental conditions, and degradation with age; segmenting the associated sensor probability distribution for each sensor into sub-ranges, wherein every sub-range is represented by an uncertainty boundary segment; for each sub-range,_assigning a probability measure reflective of the reliability of each sensor to sense the position of the object; using statistical simulation to manipulate the probability measures associated with each sub-range of each sensor to generate a value indicative of the most likely position of the object and an associated probability distribution for the most likely position of the object; applying a conjunctive fusion method to_the estimated position of the object from each of the plurality of sensors and the associated sensor probability distributions to identify an intersection region of the sub-ranges with the most likely probability of defining the position of the object.