A multi-sensor data fusion system and method provides adaptive weighting of the contributions from a plurality of sensors in the system using an additive calculation of a sensor reliability function for each sensor. During a predetermined tracking period, data is received from each individual sensor in the system and a sensor reliability function is determined for each sensor based on the SNR (signal-to-noise ratio) for the received data from each sensor. Each sensor reliability function is individually weighted based on the SNR for each sensor and a comparison of predetermined sensor operation characteristics for each sensor and a best performing (most reliable) sensor. Additive calculations are performed on the sensor reliability functions to produce both an absolute and a relative reliability function which provide a confidence level for the multi-sensor system relating to the correct classification (recognition) of targets and decoys.
The first sensor collects a first group of first sensor readings of first fixed size dependent on a range of a first sensor and safeguarding requirements of a vehicle. A second sensor collects a second group of second sensor readings of second fixed size dependent on a range of a second sensor and the safeguarding requirements. A reference frame manager references the first group and the second group of readings to a vehicle coordinate reference frame. An integration module establishes a composite grid referenced to the ground based on a spatially aligned integration of the readings of the first group and the second group. A update module refreshes the composite grid upon material movement of the vehicle such that the global occupancy of each cell in the composite grid varies in accordance with the particular location of the vehicle on the terrain.
