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A modified block FTF adaptive algorithm with applications to underwater target detection

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2 Author(s)
Hasan, M.A. ; Dept. of Electr. Eng., Colorado State Univ., Fort Collins, CO, USA ; Azimi-Sadjadi, M.R.

In this paper, the problem of weighted block recursive least squares (RLS) adaptive filtering is formulated in the context of a 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

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Signal Processing, IEEE Transactions on  (Volume:44 ,  Issue: 9 )