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Improved delay-locked loop in random-modulation continuous-wave laser ranging.

Bo Gao, Shaotang Wei, Jiahui Guo

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Summary

This summary is machine-generated.

This study enhances laser ranging precision for autonomous driving using a novel delay-locked loop (DLL) model. The improved DLL achieves millimeter-level accuracy, overcoming limitations in modulation and sampling rates for better performance.

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Area of Science:

Optics and Photonics
Robotics and Autonomous Systems
Signal Processing

Background:

Random-modulation continuous-wave (RMCW) laser ranging offers high data rates and signal-to-noise ratio (SNR), crucial for autonomous driving.
Current RMCW laser ranging precision is limited by modulation and sampling rates.
The delay-locked loop (DLL) is a robust data processing technique utilized in global positioning systems.

Purpose of the Study:

To enhance the precision of RMCW laser ranging for autonomous driving applications.
To adapt and improve the delay-locked loop (DLL) algorithm for RMCW laser ranging.
To validate the improved DLL model through theoretical analysis and experimental verification.

Main Methods:

Introduced a delay-locked loop (DLL) data processing method adapted from global positioning systems.
Conducted analysis of a matched filter to refine the DLL model.
Performed rigorous experimental verification to align the improved DLL model with real-world observations.

Main Results:

Achieved a precision of 4.27 mm at a signal-to-noise ratio (SNR) of 34.17 dB.
Demonstrated significantly improved ranging precision compared to existing methods.
Exhibited outstanding performance in laser imaging experiments.

Conclusions:

The improved DLL model effectively enhances RMCW laser ranging precision for autonomous driving.
The adapted DLL technique overcomes previous limitations related to modulation and sampling rates.
This advancement holds significant potential for improving the safety and reliability of autonomous vehicles.