Abstract

With the rapid development of autonomous vehicles and mobile robotics, the desire to advance robust light detection and ranging (Lidar) detection methods for real world applications is increasing. However, this task still suffers in degraded visual environments (DVE), including smoke, dust, fog, and rain, as the aerosols lead to false alarm and dysfunction. Therefore, a novel Lidar target echo signal recognition method, based on a multi-distance measurement and deep learning algorithm is presented in this paper; neither the backscatter suppression nor the denoise functions are required. The 2-D spectrogram images are constructed by using the frequency-distance relation derived from the 1-D echo signals of the Lidar sensor individual cell in the course of approaching target. The characteristics of the target echo signal and noise in the spectrogram images are analyzed and determined; thus, the target recognition criterion is established accordingly. A customized deep learning algorithm is subsequently developed to perform the recognition. The simulation and experimental results demonstrate that the proposed method can significantly improve the Lidar detection performance in DVE.

Highlights

  • Light detection and ranging (Lidar) sensors are widely used in detection applications, such as autonomous driving [1,2,3] and unmanned ground vehicles (UGV) [4], due to the characteristics of high resolution [5] and precision [6]

  • When they are applied in degraded visual environments (DVE), such as smoke, fog, dust, and rain, the laser signals of light detection and ranging (Lidar) sensors are attenuated and absorbed by scattering effect and extinction effect of aerosols, it is difficult to extract effective beat signals and detect the targets further [7]

  • We propose a novel target echo signal recognition method based on 2-D spectrogram images

Read more

Summary

Introduction

Light detection and ranging (Lidar) sensors are widely used in detection applications, such as autonomous driving [1,2,3] and unmanned ground vehicles (UGV) [4], due to the characteristics of high resolution [5] and precision [6]. When they are applied in degraded visual environments (DVE), such as smoke, fog, dust, and rain, the laser signals of Lidar sensors are attenuated and absorbed by scattering effect and extinction effect of aerosols, it is difficult to extract effective beat signals and detect the targets further [7]. Donoho et al [9]

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call