Extended LIDAR Detection Periods for Range Ambiguity
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Solution Overview
Problem
LIDAR devices face range aliasing issues, where they cannot disambiguate between signals from different ranges, leading to false echoes and incorrect distance measurements for objects outside their nominal detection range.
Innovation Solution
Implementing extended detection periods in the LIDAR system, allowing the computing system to determine if detected return light pulses reflect off objects beyond the nominal range by comparing the time delays of these pulses to the emission times, and using this information to adjust the detection range and overcome range ambiguity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the LIDAR device uses standard detection periods to establish nominal detection range, then the device complexity and processing speed are maintained, but range aliasing occurs and measurement precision deteriorates for objects outside nominal range
Solution Approach 1:
The detection period is segmented into multiple types: standard detection periods for normal operation and extended detection periods for detecting objects beyond nominal range. This segmentation allows the system to maintain normal operation while periodically checking for range aliasing conditions without continuously operating in extended mode, thus balancing precision improvement with complexity management.
Solution Approach 2:
Extended detection periods are implemented periodically rather than continuously. The system alternates between standard detection periods and extended detection periods, allowing it to detect objects beyond nominal range when needed while maintaining overall system efficiency and avoiding the continuous overhead of extended detection complexity.
2Measurement precision
If extended detection periods are used to detect objects beyond nominal range, then measurement precision and detection range are improved, but device complexity increases
Solution Approach 1:
The detection period structure is made dynamic by adaptively selecting between standard and extended detection periods based on operational needs. The system can adjust the frequency and timing of extended detection periods, allowing flexibility in balancing precision requirements against complexity constraints for different operating scenarios.
Solution Approach 2:
The detection period parameter is changed from a fixed standard duration to a variable duration that can be extended when needed. By modifying the detection period length parameter dynamically, the system achieves improved measurement precision for distant objects without permanently increasing the complexity of the detection structure.
3Productivity
If standard detection periods are used, then processing speed and productivity are maintained, but range aliasing causes loss of information about objects outside nominal range
Solution Approach 1:
Extended detection periods perform preliminary detection of objects that may be beyond the nominal range before standard detection periods would misinterpret them. By proactively detecting these objects during extended periods, the system prevents information loss without requiring every detection cycle to use extended periods, thus maintaining overall processing speed.
Solution Approach 2:
The system uses feedback from extended detection periods to identify and correct range aliasing conditions. When objects are detected during extended periods that would be misinterpreted during standard periods, this feedback information is used to adjust detection parameters or interpret subsequent detections more accurately, preventing ongoing information loss while maintaining productivity.
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
This approach effectively extends the detection range of the LIDAR device, reducing computational costs and improving accuracy in identifying objects outside the nominal range, thereby enhancing autonomous vehicle navigation and object detection.
Implementation Method 1
detecting a returning pulse, if any, reflected from an object in the environment
Implementation Method 2
determining the distance to the object according to the time delay between the transmitted pulse and the reception of the reflected pulse
Data Source
AI summary
A computing system may operate a LIDAR device to emit and detect light pulses in accordance with a time sequence including standard detection period(s) that establish a nominal detection range for the LIDAR device and extended detection period(s) having durations longer than those of the standard detection period(s). The system may then make a determination that the LIDAR detected return light pulse(s) during extended detection period(s) that correspond to particular emitted light pulse(s). Responsively, the computing system may determine that the detected return light pulse(s) have detection times relative to corresponding emission times of particular emitted light pulse(s) that are indicative of one or more ranges. Given this, the computing system may make a further determination of whether or not the one or more ranges indicate that an object is positioned outside of the nominal detection range, and may then engage in object detection in accordance with the further determination.