Vehicular Ad-hoc Networks (VANET) rely on Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication to improve road safety and traffic efficiency. Therefore, malicious data could jeopardize the benefits of VANET communication. Hence, a data-centric misbehavior detection system should be deployed on each on-board unit to improve confidence in the received data. In this paper, we investigate the potential of using Pearson Correlation to detect location forging attacks. We analyze four location forging attacks and discuss how the correlation matrix detect them. The proposed solution works in real-time, without any training, but, depending on the type of road, requires at least four to seven seconds of history to be fully effective. Experiments are performed on real datasets from Wyoming Connected Vehicle Pilot Deployment and from University of Michigan Transportation Research Institute.