Recent advances in ultrasound imaging triggered by transmission of ultrafast plane waves have rendered functional ultrasound (fUS) imaging a valuable neuroimaging modality capable of mapping cerebral vascular networks, but also for the indirect capture of neuronal activity with high sensitivity thanks to the neurovascular coupling. However, the expansion of fUS imaging is still limited by the difficulty to identify cerebral structures during experiments based solely on the Doppler images and the shape of the vessels. In order to tackle this challenge, this study introduces the vascular brain positioning system (BPS), a GPS of the brain. The BPS is a whole-brain neuronavigation system based on the on-the-fly automatic alignment of ultrafast ultrasensitive transcranial Power Doppler volumic images to common templates such as the Allen Mouse Brain Common Coordinates Framework. This method relies on the online registration of the complex cerebral vascular fingerprint of the studied animal to a pre-aligned reference vascular atlas, thus allowing rapid matching and identification of brain structures. We quantified the accuracy of the automatic registration using super-resolution vascular images obtained at the microscopic scale using Ultrasound Localization Microscopy and found a positioning error of 44 µm and 96 µm for intra-animal and inter-animal vascular registration, respectively. The proposed BPS approach outperforms the manual vascular landmark recognition performed by expert neuroscientists (inter-annotator errors of 215 µm and 259 µm). Using the online BPS approach coupled with the Allen Atlas, we demonstrated the capability of the system to position itself automatically over chosen anatomical structures and to obtain corresponding functional activation maps even in complex oblique planes. Finally, we show that the system can be used to acquire and estimate functional connectivity matrices automatically. The proposed functional ultrasound on-the-fly neuronavigation approach allows automatic brain navigation and could become a key asset to ensure standardized experiments and protocols for non-expert and expert researchers.