Data-space preconditioning

This is equivalent to pre-multiplying the matrix L and the data vector ${\bf d}$ by a diagonal matrix ${\bf R^{-1}}$and solving the system:

$$\bold R^{-1} \bold d = \bold R^{-1} \bold L \bold m \EQNLABEL{dat-prec}$$ (55)

where the sums of the elements from each row of L are along the diagonal of ${\bf R}$.

Since each row corresponds to a summation surface (impulse response of $\bold L^T$), then ${\bf R^{-1}}$ is normalization by the coverage before AMO.