Abstract
Walking error has been problematic for pulsed LiDAR based on a single threshold comparator. Traditionally, walk error must be suppressed by some time discrimination methods with extremely complex electronic circuits and high costs. In this paper, we propose a compact and flexible method for reducing walk error and achieving distance-intensity imaging. A single threshold comparator and commercial time digital converter chip are designed to measure the laser pulse’s time of flight and pulse width. In order to obtain first-class measurement accuracy, we designed a specific pulse width correction method based on the Kalman filter to correct the laser recording time, significantly reducing the ranging walk error by echo intensity fluctuation. In addition, the pulse width obtained by our method, which is a recording of the laser intensity, is conducive to target identification. The experiment results verified plane point clouds of various targets obtained by the proposed method with a plane flatness less than 0.34. The novel contribution of the study is to provide a highly integrated and cost-effective solution for the realization of high-precision ranging and multi-dimensional detection by pulsed LiDAR. It is valuable for realizing multi-dimension, outstanding performance, and low-cost LiDAR.
Highlights
The basic principle of pulsed laser ranging is that the laser pulse is actively fired to the target, the laser echo of the illuminated point on the target is detected, the flight time of the laser pulse is measured, and the distance information of the target is calculated.Pulsed laser detection and ranging (LiDAR) has the advantages of high peak power of laser emission, long detection distance, and a low requirement on the coherence of the light source
By measuring the laser pulse width, and combined with machine learning compensated time of laser’s flight of time, the range measurement accuracy of the lidar is improved effectively, and the time drift caused by the fluctuation of laser pulse echo intensity is obviously reduced
It relies on a simple single threshold comparator circuit and time digital converter (TDC)-GP22 chip to measure the laser pulse’s leading-edge time interval and echo pulse width
Summary
The basic principle of pulsed laser ranging is that the laser pulse is actively fired to the target, the laser echo of the illuminated point on the target is detected, the flight time of the laser pulse is measured, and the distance information of the target is calculated. Yeon Ji et al [7] presented a deep learning (DL) approach with LiDAR data to aid autonomous navigation for UAVs in completely unknown, GPS-denied indoor environments These applications are based on LiDAR’s basic ranging function. In this paper, aiming to simultaneously improve the accuracy of LiDAR’s analog time discrimination method and its robustness to laser pulse intensity fluctuation, we designed a time discrimination and measurement circuit with a single threshold comparator and TDC-GPX2 timing chip. By measuring the laser pulse width, and combined with machine learning compensated time of laser’s flight of time, the range measurement accuracy of the lidar is improved effectively, and the time drift caused by the fluctuation of laser pulse echo intensity is obviously reduced. To verify the feasibility and performance of our design, a series of experiments were carried out as follows
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