From distance to depth: The evolution of time-of-flight sensing

23 Sep 2026

From distance to depth: The evolution of time-of-flight sensing

Many embedded systems only need to know whether an object is present. Increasingly, however, applications such as robotics, smart lighting, home appliances, smartphones, wearables, building automation, and industrial equipment require a deeper understanding of their surroundings. Instead of a simple yes-or-no detection, engineers are looking for information about distance, object position, and scene geometry.

Direct Time-of-Flight (dToF) sensing addresses this challenge by measuring the time it takes for a pulse of light to travel to an object and back to the sensor. By measuring this round-trip travel time with extremely high precision, dToF systems can calculate distances accurately and provide spatial information about the environment.

From single-point ranging to depth maps

Historically, dToF sensing has been used in applications where a single distance measurement is sufficient. Examples include smartphone camera autofocus, presence detection, and object ranging. By providing accurate distance information independent of object texture or contrast, dToF can help camera systems achieve fast and reliable autofocus, including in challenging lighting conditions.

Advances in SPAD (Single-Photon Avalanche Diode) technology and timing electronics are now extending dToF beyond single-point measurements. Modern multi-zone dToF systems divide the field of view into multiple measurement zones, allowing distance information to be captured across a scene simultaneously.

Rather than reporting a single distance value, these systems can generate simplified depth maps that provide spatial awareness.

Applications range from obstacle avoidance in robotics and object tracking in industrial systems to occupancy sensing in smart buildings, gesture recognition in consumer devices, and adaptive smart lighting that reacts to the location and movement of people within a room.

Measuring distance in real-world conditions

Accurate optical ranging becomes more challenging outside the lab. Ambient sunlight, highly reflective or dark surfaces, multiple objects within the field of view, and contamination on the optical window can all affect measurement quality.

To address these challenges, modern dToF architectures combine SPAD-based photon detection with signal-processing techniques that analyze the temporal distribution of returning photons. Histogram-based processing can help distinguish multiple reflections and extract meaningful depth information even in complex environments.

As dToF technology continues to evolve, it is increasingly bridging the gap between simple proximity sensors and vision-based systems. Multi-zone depth sensing enables embedded devices to better understand their surroundings while avoiding the complexity of a full camera-based imaging solution.