Multisensor fusion based on decision-making in INS/CCD/SAR integrated systems

This paper presents a novel multisensor fusion method using the fuzzy ARTMAP neural network and Dempster-Shafer theory of evidence in INS/CCD/SAR (inertial navigation system/optical charged device/synthetic aperture radar) integrated systems. In this method, the CCD and SAR systems work independently. Fusion work takes effect in the decision-making level, not in the pixel level. First, this method use fuzzy ARTMAP NN to classify both the CCD and SAR real-time images according to the image quality, then those 'good' real-time images are matched with CCD and SAR reference images respectively, and matching positions obtained; and then, the two matching positions are fused by the D-S theory of evidence to judge which position is more accurate; finally, the fusion result is integrated with INS to attain the optimal state estimation of navigation/guidance parameters. Simulation results show that this fusion method can improve the precision of the end guidance system.