Utilizing browsers to identify and track users has become a routine on the Web in recent years. It is easy for the browser to collect sensitive information and construct comprehensive user profiles while the users are still unaware. As the problem mentioned above, several anti-fingerprint mechanisms have been adopted to protect user privacy. However, our research finds a novel method based on localization fingerprints that may still threaten user privacy. The location fingerprint obtains the response delay of data transmission over the link between the users and the third-party sites. Since the physical link state information between the host and the remote website is distinct and steady, it can be used to extract statistical features and construct user profiles. We implement a multilateration cross-site image resource request scheme to collect link-state information of users and develop a prototype called PingLoc to evaluate the effectiveness. About 1,093 users from all over the world are involved in our experiment. The evaluation shows that the delay features collected are stable, and the accuracy of the localization fingerprint is up to 98%. Pressure testing shows that the PingLoc is robust against various anti-fingerprint mechanisms and achieves 93.5% accuracy for browser switching, 80.6% accuracy for virtual machine disguising, and 88.2% accuracy for IP rotation.