This paper proposes the use of negative detection information to improve multirobot Markov localization. In multirobot localization, the pose beliefs of two robots are updated whenever one robot detects another one and measures their relative distance. Negative detection information means absence of detection information and in general is not used in the updating of pose beliefs. However, it can also be informative and we argue that this information should be incorporated into the localization approach. We contribute to a negative detection model and show how it can be integrated into cooperative multirobot Markov localization. Experimental results show that the use of negative detection information leads to an improvement of localization accuracy.