LiDAR Time-Division Scanning for Crosstalk-Free Point Clouds
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Solution Overview
Problem
Lidar devices face issues with crosstalk, particularly due to high-intensity return signals from reflective objects, leading to detection errors and false positives, which existing mitigation strategies may not fully address without degrading performance.
Innovation Solution
Implementing a method involving two emission cycles with corresponding detection cycles, where all light emitters emit signals in the first cycle for long-range detection and subsets emit signals in the second cycle for short-range detection, allowing for identification and removal of crosstalk by comparing datasets from both cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If all light emitters emit signals simultaneously for long-range detection, then detection coverage is improved, but crosstalk between detection channels increases
Solution Approach 1:
The detection process is segmented into multiple time-division cycles. In each cycle, only subsets of light emitters and corresponding light detectors are activated simultaneously, while other channels remain inactive. This temporal segmentation allows full detection coverage to be achieved across multiple cycles without the crosstalk problems that would result from all channels operating simultaneously.
Solution Approach 2:
The system employs periodic detection cycles where different subsets of emitter-detector pairs are activated in alternating time periods. This periodic activation pattern ensures that each channel gets its designated time slot for detection while preventing overlap with other channels, thereby eliminating crosstalk while maintaining comprehensive detection coverage over time.
2Measurement precision
If time-division multiple access scanning is implemented to mitigate crosstalk, then detection accuracy is improved, but detection time increases
Solution Approach 1:
In each time-division cycle, only a subset of emitter-detector pairs is activated rather than all channels. This partial action reduces crosstalk and improves detection accuracy for the active channels. By strategically selecting which subsets to activate in each cycle and repeating across multiple cycles, the system achieves accurate detection without requiring all channels to operate simultaneously, thus managing the time trade-off effectively.
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 mitigates crosstalk, enhancing the accuracy of lidar data by separating detection events in time, thereby improving the reliability of point cloud generation and reducing false detections.
Implementation Method 1
The first group of reflected light signals corresponds to reflections of the first group of light signals from objects in the surrounding environment
Implementation Method 2
detecting, by a first group of light detectors of the lidar device during a first listening window, a first group of reflected light signals
Data Source
Figure 1
Figure 2A~2B
Figure 2C~2D
AI summary
Example embodiments relate to time-division multiple access scanning for crosstalk mitigation in a light detection and ranging (lidar) device (410). An example embodiment includes a method comprising: emitting a first group of light signals into a surrounding environment. The first group of light signals corresponds to a first angular resolution; detecting, during a first listening window, a first group of reflected light signals; emitting a second group of light signals into the surrounding environment. The second group of light signals corresponds to a second angular resolution with respect to the surrounding environment. The second angular resolution is lower than the first angular resolution; detecting a second group of reflected light signals from the surrounding environment; and synthesizing, by a controller (416) of the lidar device (410), a dataset usable to generate one or more point clouds. The controller (416) controls a plurality of light emitters (424) and a plurality of light detectors (426). The lidar device (410) further includes a firing circuit (428) to select and provide power to respective light emitters of the plurality of light emitters (424) and may include a selector circuit (430) to select respective light detectors of the plurality of light detectors (426). A firing cycle of the lidar device (410) may include the first cycle followed by the second cycle. By comparing the ranges represented by the detected light signals during the two cycles, signals corresponding to crosstalk can be identified and/or removed from a resulting dataset.