LiDAR Time-Division Scanning for Crosstalk Mitigation
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Solution Overview
Problem
Lidar devices experience crosstalk noise due to high-intensity return signals from reflective objects, leading to false positive detections and missed detections, which can impair the accuracy of object detection and navigation.
Innovation Solution
Implement a two-cycle emission and detection strategy in lidar devices, where the first cycle emits all channels for long-range detection and the second cycle uses subsets of channels for shorter-range detection, allowing for crosstalk identification and mitigation by comparing results from both cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If all light emitters emit light signals simultaneously for long-range detection, then the detection range is extended, but crosstalk noise increases due to high-intensity return signals
Solution Approach 1:
The patent segments the detection process into two distinct cycles: a first cycle where all light emitters operate for long-range detection, and a second cycle where subsets of light emitters operate for short-range detection. This segmentation allows the system to separate long-range and short-range detection functions, enabling crosstalk mitigation by comparing results from both cycles while maintaining extended detection range capability.
Solution Approach 2:
The patent implements periodic action by alternating between two emission cycles with different detection strategies. The first cycle uses all light emitters for long-range detection, while the second cycle uses subsets for short-range detection. This periodic switching enables the system to identify and remove crosstalk signals by comparing detections from both cycles, thereby reducing crosstalk noise while maintaining long-range detection capability.
2Object-generated harmful factors
If subsets of light emitters are used for short-range detection, then crosstalk is reduced, but angular resolution decreases
Solution Approach 1:
The patent merges the results from two different detection cycles to achieve both crosstalk reduction and maintained angular resolution. The first cycle provides long-range detection data with full angular resolution using all light emitters, while the second cycle provides short-range detection data with reduced crosstalk using subsets of light emitters. By combining and comparing these results, the system achieves accurate object detection with both crosstalk mitigation and preserved angular resolution.
Solution Approach 2:
The patent employs feedback by comparing detection results from the first cycle (all emitters, long-range) with results from the second cycle (subsets of emitters, short-range). This comparison provides feedback that enables the system to identify crosstalk signals and distinguish them from genuine reflections, thereby maintaining measurement precision while reducing crosstalk noise through iterative verification.
3Measurement precision
If two emission cycles are performed for crosstalk mitigation, then detection accuracy is improved, but detection time increases
Solution Approach 1:
The patent applies partial action in the second emission cycle by using only subsets of light emitters rather than all emitters. This partial operation reduces the computational and processing burden compared to full-emitter operation, thereby mitigating the time penalty associated with performing two cycles. The subset-based approach maintains sufficient detection accuracy for crosstalk identification while minimizing the time overhead.
Solution Approach 2:
The patent discards redundant detection data by comparing results from both cycles and keeping only the valid, non-crosstalk signals. By identifying and discarding crosstalk-contaminated detections from the first cycle using information from the second cycle, the system recovers accurate detection results without requiring full processing of all data from both cycles, thereby reducing the overall detection time while maintaining accuracy.
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 reduces crosstalk noise, enhancing the accuracy of lidar detection by distinguishing genuine signals from crosstalk, thereby improving the reliability of object detection and navigation systems.
Implementation Method 1
detecting, by a first group of light detectors of the lidar device during a first listening window, a first group of reflected light signals from the surrounding environment. 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
emitting, from a first group of light emitters of a light detection and ranging (lidar) device, a first group of light signals into a surrounding environment
Data Source
AI summary
Example embodiments relate to time-division multiple access scanning for crosstalk mitigation in light detection and ranging (lidar) devices. An example embodiment includes a method. The method includes emitting a first group of light signals into a surrounding environment. The first group of light signals corresponds to a first angular resolution. The method also includes detecting, during a first listening window, a first group of reflected light signals. Additionally, the method includes 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. Further, the method includes detecting a second group of reflected light signals from the surrounding environment. In addition, the method includes synthesizing, by a controller of the lidar device, a dataset usable to generate one or more point clouds.