In this paper, we describe the easy and robustness self-position estimation technique against an unknown obstacle under the environment where many unknown obstacles exist. The free-space observation model is suggested as the technique of estimating a self-position in an environment with many unknown obstacles, such as a pedestrian. This has realized robust self-position estimation. However, the free-space observation model has a several problem that complicated likelihood evaluation, particle continues being spread and it cannot be converge when a immovable obstacle is able to observe either only right-and-left to a robot’s direction of movement. In this research, we solve these problem with two likelihood evaluations that the based on the area of free space and based on the area of occupied space. We evaluate robustness and verify the validity of suggestion method by the simulation and the experiment under the real environment.