How a Smart LIDAR System Adapts to Noise for Better Distance Sensing

This patent describes a LIDAR system that uses multiple lasers and detectors, and intelligently adjusts the electrical settings of specific detectors to reduce noise and improve distance measurements in different lighting conditions.

What it covers

This LIDAR system works by having several lasers that can each light up a specific area (claim 41a). A controller decides which of these lasers to fire, creating light in a 'desired illumination region' (claim 41b). An optical receiver, with many detectors, is positioned to catch the light returning from this illuminated area (claim 41c). The system then measures how long the light took to travel (time-of-flight) to calculate distances. The clever part is that a receiver controller adjusts the electrical 'bias point' of specific detectors or groups of detectors (sub-arrays) based on which area is being illuminated (claim 41d). For example, if a specific area is very bright due to sunlight, the system can adjust the detectors looking at that area to reduce the impact of that background light, improving accuracy.

What it doesn't cover

• —Does not cover LIDAR systems that use only a single laser or a single detector.
• —Does not cover LIDAR systems where the detector's electrical settings (bias point) are fixed and not adaptively changed based on the illuminated region.
• —Does not cover LIDAR systems that rely on mechanical scanning mirrors to steer a single laser beam, as this patent describes a system with a 'plurality of lasers' and 'solid-state' in its description.
• —Does not cover systems that do not measure range information from time-of-flight measurements.
• —Does not cover systems where the transmitter controller does not selectively pulse desired lasers to generate light in a specific region.

The clever bit

The truly novel aspect is the adaptive biasing of specific detectors or detector sub-arrays. The system dynamically adjusts the electrical settings of the light sensors based on which part of the scene is currently being illuminated, allowing it to optimize signal detection and minimize noise for that particular region.

Why it matters

LIDAR technology is crucial for applications like self-driving cars, robotics, and advanced mapping, as it provides precise 3D information about the environment. This patent addresses a key challenge in LIDAR: dealing with varying light conditions and background noise. By adaptively adjusting detector sensitivity, the system can maintain accuracy in diverse environments, from bright daylight to low light, making it more reliable for safety-critical applications.

Real-world examples

• 1.Autonomous vehicle perception systems
• 2.Robotics navigation and obstacle avoidance
• 3.Industrial automation and safety systems
• 4.Advanced driver-assistance systems (ADAS)
• 5.Drone-based mapping and surveying