Improved square-root forms of fast linear least squares estimation algorithms

A technique for improving the numerical stability of vector lattice algorithms is presented. It consists of replacing the J-orthogonal transformations used in standard SRF (square-root form) algorithms by orthogonal ones, which provides a better robustness to round-off errors. To illustrate the generality of the approach, explicit modified SRFs of the generalized Levinson algorithm and the Chandrasekhar equations are derived. Simulations confirm the gain in numerical stability, which is obtained at a relatively small extra cost.<
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