A modified block FTF adaptive algorithm with applications to underwater target detection Hasan, Mohammed A. ; Azimi-Sadjadi, Mahmood R. "This work was supported by the Office of Naval Research. Technical agent was Naval Coastal Systems Station, Panama City, FL." In this paper, the problem of weighted block recursive least squares (RLS) adaptive filtering is formulated in the context of block fast transversal filter (FTF) algorithm. This “modified block FTF algorithm” is derived by modifying the constrained block-LS cost function to guarantee global optimality. This new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data. The tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. This algorithm is computationally more efficient compared with other LS-based schemes. The effectiveness of this algorithm is tested on a real-life problem dealing with underwater target identification from acoustic backscatter. The process involves the identification of the presence of resonance in the acoustic backscatter from a target of unknown shape submerged in water. Colorado State University. Libraries 1996 text ; image application/pdf ECEmra00042.pdf FACFECEN100522ARTI eng c1996 IEEE
A modified block FTF adaptive algorithm with applications to underwater target detection
Hasan, Mohammed A. ; Azimi-Sadjadi, Mahmood R.
"This work was supported by the Office of Naval Research. Technical agent was Naval Coastal Systems Station, Panama City, FL."
In this paper, the problem of weighted block recursive least squares (RLS) adaptive filtering is formulated in the context of block fast transversal filter (FTF) algorithm. This “modified block FTF algorithm” is derived by modifying the constrained block-LS cost function to guarantee global optimality. This new soft-constrained algorithm provides an efficient way of transferring weight information between blocks of data. The tracking ability of the algorithm can be controlled by varying the block length and/or a soft constrained parameter. This algorithm is computationally more efficient compared with other LS-based schemes. The effectiveness of this algorithm is tested on a real-life problem dealing with underwater target identification from acoustic backscatter. The process involves the identification of the presence of resonance in the acoustic backscatter from a target of unknown shape submerged in water.
Colorado State University. Libraries
1996
text ; image
application/pdf
ECEmra00042.pdf
FACFECEN100522ARTI
eng
c1996 IEEE