Target Tracking and Fusion Using Imaging Sensor and Ground Based Radar Data 2005-5842

An image centroid tracking algorithm (ICTA) has been implemented in PC MATLAB13; for target tracking based on the data obtained from an imaging sensor. The gray level image13; is converted into binary image using the segmentation technique and reduced into clusters13; using nearest neighbor criterion. Nearest neighborhood Kalman filter and Probabilistic data13; association filter are employed for state estimation using centroid measurement of clusters.13; The simulated results showed that it is possible to achieve tracking accuracies of 0.52 pixels13; root mean square error in position and 0.2 pixels/frame in velocity. Performance of this13; algorithm is evaluated using several statistical criteria. ICTA has been extended to multisensor13; scenario, where the trajectories obtained from the imaging sensor are fused with13; those from a ground based radar using track-to-track fusion technique.