The ability to achieve subpixel peak location accuracy for point source taraets in the cross-scan direction for scanning sensors and in both directions for staring sensors is examined systematically by means of Monte Carlo experiments. The performance of three peak location algorithms (simple centroid, extended centroid, polynomial least squares fit) is tested for sensitivity to system signal-to-noise ratio, detector deadspace, and blur spot size relative to detector size. A symmetrical, gaussian intensity profile of the blur spot is used in all cases. Computational efficiency, in terms of the number of multiplies and adds required, was considered in selecting the algorithms to be compared. Overall, we found that the simple centroid algorithm provides the optimum performance, giving %1/10 pixel accuracy for S/N=10 and no deadspace. In addition, performance improves for the centroid algorithms and degrades for the least squares fit algorithm as the blur spot size increases. Increasing deadspace markedly degrades the performance of the centroid algo-rithms.