Multiresolutional multisensor target identification

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.<<ETX>>

[1]  Lang Hong Adaptive distributed filtering in multicoordinated systems , 1991 .

[2]  M. Desai,et al.  Acoustic transient analysis using wavelet decomposition , 1991, [1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering.

[3]  K. C. Chou,et al.  Multiscale recursive estimation, data fusion, and regularization , 1994, IEEE Trans. Autom. Control..

[4]  I. Daubechies Orthonormal bases of compactly supported wavelets , 1988 .

[5]  Lang Hong Multiresolutional filtering using wavelet transform , 1993 .

[6]  J. Andel Sequential Analysis , 2022, The SAGE Encyclopedia of Research Design.