Orthogonal Time Frequency and Space (OTFS) modulation-based system for Integrated Sensing and Communication (ISAC) in vehicular scenarios is a promising technology and is expected to provide reliable communication in high-speed environments. A vehicle-to-infrastructure-based OTFS multi-static system with single or multiple transmitters is considered in this work. The cell towers communicate to the intended target vehicle(s) and simultaneously estimate the location, velocity, and bistatic radar cross-section of other targets in the scene. Bringing in a multi-static framework gives the advantage of exploiting spatial diversity for better target detection. Pilot sequences are chosen to ensure both spectral efficiency and accurate detection and parameter estimation by using the signals from multiple transmitters. However, in the case of multiple targets, associating measurements to targets is critical in multi-static systems. The prime problem of multi-target data association is solved by a joint association and localization approach using a sparse recovery framework. Simulations are performed with real-time system and signal parameters. Performance of the algorithm for various OTFS Delay-Doppler block-size configurations and multiple targets of different bistatic radar cross-sections is demonstrated. The performance and complexity comparison with other existing data association approaches are furnished. The results highlight better accuracy with lesser complexity, thus aiding in the practical implementation of an ISAC system. Furthermore, the extension of our algorithm to accommodate fractional bistatic delay and Doppler measurements is also described so that enhanced performance can be achieved even with only modest bandwidth requirements.