Time-of-Flight Sensor Depth Disambiguation via Dynamic Modulation
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Solution Overview
Problem
Time-of-flight sensors are unreliable in environments with varied lighting and multiple objects at different distances, leading to ambiguous returns and inefficient object detection, which can result in unsafe navigation for autonomous vehicles.
Innovation Solution
The implementation of integration time alteration and modulation frequency variation techniques for time-of-flight sensors, combined with disambiguation methods, to improve intensity and depth data accuracy, allowing for more reliable object detection and navigation in complex environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If time-of-flight sensors are used in environments with varied lighting and multiple objects at different distances, then object detection capability is provided, but measurement reliability deteriorates due to ambiguous returns
Solution Approach 1:
The patent segments the measurement process into multiple discrete time gates, where each gate captures depth information from a specific distance range. By dividing the overall detection task into segmented temporal measurements, the system can distinguish between multiple objects at different distances that would otherwise appear as ambiguous returns in a single continuous measurement
Solution Approach 2:
The patent employs periodic modulation of the light source at specific frequencies and uses synchronous detection to measure depth. By using periodic action with multiple modulation frequencies and time-gated detection, the system can resolve ambiguous depth measurements and distinguish between objects at different distances, improving measurement reliability in complex environments
2Productivity
If time-of-flight sensors are designed to detect objects in predetermined distance ranges, then detection efficiency is improved, but adaptability to multiple distance ranges deteriorates
Solution Approach 1:
The patent dynamically adjusts the time gate windows and modulation frequencies based on the detection requirements. By making the measurement parameters dynamic rather than fixed, the system can efficiently detect objects across multiple distance ranges without requiring separate sensor designs for each range, thus maintaining detection efficiency while improving adaptability
Solution Approach 2:
The patent changes measurement parameters such as time gate duration, gate spacing, and modulation frequency to adapt to different detection scenarios. By varying these parameters, the sensor can optimize its performance for different distance ranges and environmental conditions, achieving both efficiency and versatility
3Measurement precision
If integration time is increased to improve intensity data accuracy, then intensity measurement precision is improved, but depth measurement ambiguity increases due to multiple object returns
Solution Approach 1:
The patent segments the integration period into multiple time gates, allowing intensity and depth measurements to be captured at different temporal windows. This segmentation enables the system to accumulate intensity signals over extended periods while maintaining clear depth discrimination by assigning different time gates to different distance ranges, thus improving intensity precision without increasing depth ambiguity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
These techniques enhance the accuracy and reliability of sensor data, enabling safer and more confident vehicle control by disambiguating depth measurements and improving intensity information, thereby improving object detection and navigation in environments with multiple objects at varying distances.
Implementation Method 1
Time-of-flight sensors may be unreliable in certain environments
Implementation Method 2
depth information determined based on a phase difference between the emitted carrier signal and the modulated carrier signal
Data Source
AI summary
Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. The sensor may generate first image data at a first configuration and second image data at a second configuration. The first image data and the second image data may be combined to provide disambiguated depth and improved intensity values for imaging the environment. In some examples, the first and second configurations may have different modulation frequencies, different integration times, and/or different illumination intensities. In some examples, configurations may be dynamically altered based on depth and/or intensity information of a previous frame.