Multiresolutional multisensor target identification

Abstract

An algorithm for multiresolutional multisensor target identification is presented. It uses the computationally efficient scale sequential approach to hypothesis testing during identification and implements the inverse discrete wavelet transform to fuse data from different multiresolution sensors. The authors show that fusion leads to an increase in the probability of correct identification without a significant increase in the number of computations.<>