This letter examines line-of-sight (LOS) path identification for passive multi-target localization in multipath environments. We consider a system comprising multiple spatially distributed sensors, each transmitting a distinct waveform and using the echoes to measure the LOS and non-LOS (NLOS) delays (i.e., ranges) of the targets in the surveillance area. For simplicity, we assume a 2-D localization scenario, where each range measurement defines a circle, and measurements from different sensors create intersection points on the plane. The problem is to identify intersections that are created by LOS paths. To solve the problem, we classify the intersections into N(N - 1)/2 types, where N denotes the number of sensors. Then, an efficient clustering algorithm is proposed to efficiently identify the LOS intersections based on the type and other related attributes. Numerical results are presented to demonstrate the performance of the proposed technique in comparison with several peer methods.