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In this paper, we consider a mobile robotic network that is tasked with building a map of the objects/obstacles in an environment. We are interested in the see-through mapping of the obstacles, i.e., a mapping approach that can build the spatial variations of the occluded structures. We consider two cooperative mapping approaches based on making a small number of random or coordinated wireless channel measurements between pairs of robots. Our preliminary past research suggested that the coordinated approach may perform better than the random case. In this paper, our goal is to: 1) better understand if and to what extent this is correct and 2) validate our findings with a robotic experiment. More specifically, we show that the right approach for comparing the coordinated and random sampling patterns is to look at this problem from the perspective of optimizing the number/choice of the angular motion directions. In particular, random sampling can be considered an asymptotic case where the total number of given wireless measurements are randomly distributed over an infinite number of angles. We then establish that the total number of available channel measurements should be distributed over a small number of angles, that is bigger than or equal to the number of jump angles of the structure, with a preference given to the angles of jumps. Finally and most importantly, we validate our findings by mapping occluded structures on our campus, based on only wireless channel measurements and by using our experimental robotic setup.