Chapter 2
Time-of-Flight represents the most widely adopted active depth sensing technology, measuring distance by calculating the time light takes to travel from the sensor to an object and back. This chapter explores both indirect (iToF) and direct (dToF) architectures, their physics, implementation challenges, and commercial applications.
The core concept behind Time-of-Flight sensing is elegantly simple: light travels at a constant speed (approximately 299,792,458 meters per second in vacuum), so measuring the round-trip time of a light pulse directly yields the distance to the reflecting object. However, implementing this simple principle in a practical, compact, low-cost, and power-efficient sensor involves sophisticated engineering across optics, electronics, and signal processing.
The basic relationship between distance, time, and the speed of light is expressed mathematically as:
Where c is the speed of light and t is the round-trip time. The division by 2 accounts
for the fact that light must travel to the object and back. To measure a distance of 1 meter, for example, light
must travel 2 meters total, taking approximately 6.67 nanoseconds. This extraordinarily short time interval drives
the need for extremely precise timing electronics in ToF systems.
Indirect ToF sensors, also called continuous-wave (CW) ToF sensors, use amplitude modulation rather than direct time measurement. Instead of emitting discrete pulses and measuring their return time, iToF sensors emit continuously modulated light at a specific frequency (typically 10-100 MHz) and measure the phase shift between the emitted and received signals.
The illumination source (typically an array of near-infrared LEDs at 850nm or 940nm wavelength) is modulated with a sinusoidal or square wave pattern. When this modulated light reflects off an object and returns to the sensor, it carries a phase delay proportional to the distance traveled. By measuring this phase shift, the sensor can calculate the distance.
Where f is the modulation frequency. Rearranging to solve for distance:
A critical limitation of this approach is the maximum unambiguous range, which is determined by the modulation frequency. Once the phase shift reaches 360 degrees (2π radians), it becomes ambiguous - a phase of 370 degrees is indistinguishable from 10 degrees. The maximum unambiguous range is:
For a modulation frequency of 100 MHz, the maximum unambiguous range is approximately 1.5 meters. To extend this range, iToF sensors typically measure at two or more different modulation frequencies and resolve the ambiguity at longer distances through multi-frequency phase unwrapping, which solves the phases from each frequency jointly.
Modern iToF sensors integrate several key components on a single chip:
Direct ToF sensors measure the actual time-of-flight directly by emitting very short light pulses (nanosecond duration) and precisely measuring when the reflected pulse returns. This approach avoids the ambiguity limitations of phase-based measurement and can achieve greater accuracy and longer maximum range.
A dToF sensor emits a brief pulse of light (typically 1-10 nanoseconds in duration) and uses high-precision timing electronics to measure when photons from the reflected pulse arrive at each pixel. The most advanced dToF sensors use Single Photon Avalanche Diode (SPAD) arrays, where each pixel can detect individual photons with timing resolution of tens to hundreds of picoseconds.
The direct time measurement provides several advantages over phase-based iToF systems. First, there is no fundamental ambiguity in the measurement - the maximum range is limited only by signal strength and timing precision, not by the modulation frequency. Second, dToF is inherently more robust to multi-path interference because the sensor can distinguish between the first-returning photons (direct path) and later-arriving photons (multi-path), though this requires sophisticated histogram analysis.
Single Photon Avalanche Diodes represent a breakthrough in photon detection technology. When operated above their breakdown voltage (Geiger mode), a single photon hitting the SPAD can trigger an avalanche current that produces a detectable pulse. This provides unparalleled sensitivity - theoretically, detection of a single photon is possible.
Each SPAD pixel in a dToF sensor is paired with a Time-to-Digital Converter (TDC) that precisely measures the time between the laser pulse emission and photon detection. By accumulating many measurements (typically thousands of laser pulses per depth frame), the sensor builds a histogram of photon arrival times. The peak of this histogram corresponds to the true distance to the object.
The histogram-based approach of SPAD sensors provides unique capabilities:
Modern dToF sensors integrate:
Sony's DepthSense IMX series includes both iToF and dToF sensors for various applications. The IMX556PLR iToF sensor offers VGA resolution (640x480) at 30 fps with a range of 0.2-5 meters, targeting smartphone and robotics applications. Sony's dToF sensors, developed for Apple's iPhone Pro LiDAR scanner, provide longer range capability (up to 5 meters, per Apple) with excellent multi-path handling.
Sony's Back-Side Illuminated (BSI) pixel architecture improves quantum efficiency (the percentage of incoming photons that are detected) by placing the photodiode on the side of the chip that faces the incoming light, eliminating blockage by metal interconnects. This results in better depth accuracy, especially in low-light conditions or at longer ranges.
Samsung's ISOCELL Vizion 33D is a VGA (640x480) iToF sensor targeting depth sensing in robots, XR devices, and mobile devices. It emphasizes a compact optical format and low power consumption, aiming at applications such as face authentication, AR effects, and depth-enhanced photography. Exact optical format and power figures should be confirmed in the manufacturer's datasheet.
The Vizion sensor incorporates Samsung's ISOCELL isolation technology, which places physical barriers between adjacent pixels to reduce optical crosstalk. In ToF sensors, where each pixel must distinguish between different modulation phases, this isolation is critical for depth accuracy.
Infineon's REAL3 family targets automotive and industrial applications requiring robustness and reliability. REAL3 sensors integrate Suppression of Background Illumination (SBI) circuitry into pmd-based pixels to improve operation under strong sunlight, making them suitable for in-cabin monitoring and outdoor industrial use.
Automotive REAL3 products carry AEC-Q100 qualification and wide operating temperature ranges, and provide documentation and diagnostic features that support ISO 26262 functional safety development. Grades and temperature ranges vary by product, so confirm them in the datasheet. This level of qualification is essential for safety-critical automotive applications like driver monitoring and child presence detection.
ST's FlightSense family includes both proximity sensors (single-point dToF) and imaging sensors (array-based dToF). The VL53L5CX, for example, provides multi-zone dToF measurements at up to 60 Hz with 4x4 zones and up to 15 Hz with 8x8 zones, ideal for gesture detection and robotic obstacle avoidance.
ST's proximity sensors are ubiquitous in smartphones for laser autofocus and proximity detection. The extremely low power consumption (single-digit milliwatts) and compact package make them ideal for always-on applications.
| Parameter | iToF | dToF (SPAD) |
|---|---|---|
| Accuracy | ±5-15mm @ 2m | ±1-5mm @ 2m |
| Precision | 5-10mm (1σ) | 1-5mm (1σ) |
| Maximum Range | 5-10m (indoor) | 10-20m (outdoor) |
| Frame Rate | 30-120 fps | 15-30 fps (typical) |
| Resolution | VGA to QVGA typical | QVGA or lower |
| Sunlight Operation | Limited (requires high power) | Good (histogram filtering) |
| Multi-path Handling | Challenging (algorithmic correction) | Excellent (histogram analysis) |
| Power Consumption | 300-800mW typical | 400-1200mW typical |
| Cost | Lower (mature technology) | Higher (advanced SPAD) |
The values in the table above are representative ranges summarizing trends commonly seen in published literature and product materials; they are not values set by the standard. Actual performance varies greatly with illumination power, integration time, target reflectance, and processing algorithms, so product comparisons should use the accuracy metrics of Chapter 5 and the certification test conditions of Chapter 8.
| Sensor Model | Type | Resolution | Range | Notes |
|---|---|---|---|---|
| Sony IMX556PLR | iToF | 640x480 (VGA) | 0.2-5m | Model used in the Phase 1 sensor specification example |
| Samsung ISOCELL Vizion 33D | iToF | 640x480 (VGA) | See datasheet | Targets robotics, XR, mobile |
| Infineon REAL3 family | iToF | Varies by product (HQVGA to VGA class) | See datasheet | Automotive in-cabin and industrial, SBI |
| ST VL53L5CX | dToF | 4x4 / 8x8 zones | Up to 4m | Gestures, obstacle avoidance |
| Apple LiDAR Scanner | dToF SPAD | Undisclosed (ARKit depth map 256x192) | Up to 5m | AR environment meshing |
Accuracy values are omitted from this table because they depend on measurement distance, target, and test conditions,
making direct comparison across manufacturers difficult. To address this, WIA-SEMI-013 requires the Phase 1 sensor
specification schema to describe accuracy with three fields together: value, unit, and measurement distance
(at_distance).
Selecting between iToF and dToF depends on application requirements:
ToF technology continues to evolve rapidly. Key development directions include:
iToF and dToF as separate technology values and requires accuracy to be stated together with the measurement distance.