Radar fusion to detect targets. Part II

Adaptive neuro-fuzzy fusion of sensor data

“…The target of interest was an aircraft. In publication [3] the study is extended to the case in which the target is a ballistic object. This study differs from the previous one for the electromagnetic and the kinematics characteristics of the target.…”

Inverse problems arising in different synthetic aperture radar imaging systems and a general Bayesian approach for them

“…ii) For a multi-static case, which is paid more and more attention to for the importance of cooperation surveillance for passive radars and in remote sensing filed for space distribution of satellite-borne SAR , 1,18,19 the problem becomes making full use of multi-static and multi-frequency SAR data to achieve a higher resolution, which is called super-resolution. 20 Reference 21, 22 gave a review of recent developed fusion methods, indicating that a statistically based fusion method, relying on statical approaches which can estimate the pixel value relationship between all the input bands, can eliminate the problems of data set dependency which arises with classical fusion methods.…”