Unmanned aerial vehicles (UAVs) are active research topics, especially the nano and micro subclass. They are centimeter-size drones with minimal onboard computational capabilities. These light-weights platforms provide good agility and movement freedom in indoor environments(i.g. GPS-denied environments). However, it is still a significant challenge due to the limited onboard computational capabilities to enable autonomous navigation (or even primary obstacle avoidance abilities) using standard image sensors. Vision-based perception algorithms used routinely on standard-size drones prevent their use with state-of-the-art nano-UAVs. This work demonstrates the possibility of using a new multi-zone Time of Flight (ToF) sensor to enhance autonomous navigation with a significantly lower computational load rather than most common vision-based solutions.