Routine nonlinear estimation algorithms have problem of long calculating time and slow convergence speed

when they deal with linear system Huber estimation with great amount of data and high dimension of parameter.Firstly this paper proposes the orthogonal searching algorithm according to the character of Huber estimation

then deduces the algorithm and process to calculate Huber estimation by using orthogonal searching algorithm

finally compares orthogonal searching algorithm with classic furthest falling algorithm through simulation

and the result shows that orthogonal searching algorithm has great advantage to Huber estimation when the amount of data is great and the dimension of parameter is high.