A relative bias estimation algorithm on airborne radar networks

A practical integrated estimating algorithm is proposed for multiple dynamic airborne radar networks without common targets to modifying the systematic bias, which extended innovatively from multiple sensors registration methods on common targets. On the frame of multi-sensor data fusion, the approach on overlapping common targets can be executed using Kalman filter and Earth-Centered Earth-Fixed coordinate system (ECEF) by many targets loops and times loops. The experiment shows it has good precision and robust for short distance dynamic radar networks using high speed data link even though no overlapping coverage areas are existed. The mean of ECEF X axis bias and Y axis bias are improved perfectly when compared before and after registration.