In linear systems it is desirable that the effects of noise be eliminated to the greatest extent possible. In previous work an algorithm adapted from techniques intended to ensure the quality of positions obtained from the Global Positioning System was found to produce substantial reductions in solution error over unfiltered data; in this paper, we present an improved version of this algorithm The modified algorithm is demonstrated using a problem from robot tracking, and simulation results are presented verifying the improvement in performance