Lidar System for Spotting Retro-Reflective Objects

This patent describes a lidar system that uses a special signal processing technique to identify objects that reflect light directly back to its source, like road signs or safety vests.

What it covers

The patent details a lidar system comprising a photodetector circuit and a signal processing circuit. The photodetector senses incident light, and the signal processing circuit then analyzes the reflection of a laser pulse from a target. Crucially, the signal processing circuit includes a 'matched filter' specifically designed for 'retro-reflective targets'. This filter is tuned to recognize a reflected pulse shape that shows 'vertical clipping' compared to the original transmitted pulse. This 'vertical clipping' is a unique characteristic of retro-reflective materials. By detecting this specific clipped pulse shape, the system determines if the target is retro-reflective. For example, an autonomous car's lidar could use this to reliably identify a distant road sign.

What it doesn't cover

• —Lidar systems that only measure distance to objects without specifically identifying their retro-reflective properties.
• —Methods for detecting retro-reflective targets that do not rely on analyzing the 'vertical clipping' of the reflected laser pulse.
• —Systems that identify retro-reflectors using techniques other than a 'matched filter' tuned to a clipped pulse shape.
• —Lidar systems primarily designed for identifying non-retro-reflective objects, such as plain walls or vehicles without special reflectors.
• —General object detection or classification in lidar data that does not involve the specific retro-reflectivity analysis.

The clever bit

The novelty lies in recognizing that retro-reflective targets produce a distinct 'vertical clipping' in the reflected laser pulse shape and then designing a 'matched filter' specifically to detect this unique signature. This allows the lidar system to not just see an object, but to understand a specific optical property of that object.

Why it matters

Accurately identifying retro-reflective objects is crucial for safety and navigation in many applications, especially for autonomous vehicles. These objects, such as road signs, lane markers, and safety vests, are designed to be highly visible. A lidar system that can reliably distinguish them from other objects, even in complex environments, can significantly improve the performance and safety of self-driving cars and other robotic systems.

Real-world examples

• 1.Road signs
• 2.Safety vests
• 3.Bicycle reflectors
• 4.Autonomous vehicle perception systems
• 5.Industrial robotics for object identification