Abstract
We investigate characteristics and impacts of the mutual interference to a LiDAR using an analog true-random signal, for autonomous vehicle applications. Various LiDAR signals with a continuous-wave, a pulse light from a directly modulated laser, and a frequency-modulated continuous-wave light, were generated as the mutual interference signals. The signal patterns of the interference signal formats at the receiver of the victim LiDAR were characterized by measurement results. There exist two major impacts of the mutual interference, causing a false alarm that induces ghost targets and/or images in 3-D scanning LiDARs, and reducing the SNR that degrades detection probability of an echo signal. For quantitative analysis, we estimate the cross-correlation related to the two influences. From the results, it is confirmed that the proposed LiDAR using the random signal has the mutual interference immunity regardless of the signal formats of the interference.
Highlights
Detection-and-ranging (DAR) sensors have been applied in various fields, including object recognition, simultaneous localization and mapping (SLAM), autonomous driving, etc. [1]–[3]
We investigate two main performance degradations caused by the interference, occurring ghost targets from the false alarms and reducing the signal-to-noise ratio (SNR) that causes a decrease of the detectable range
For signal formats, we study a CW light, a pulse light from a directly modulated semiconductor laser, a frequencymodulated continuous-wave (FMCW) signal light, and a true-random signal modulated (RM) signal
Summary
Detection-and-ranging (DAR) sensors have been applied in various fields, including object recognition, simultaneous localization and mapping (SLAM), autonomous driving, etc. [1]–[3]. The probability of false alarm becomes to the desired probability PrF (initial setting), and does not change by the different interference light power Pint due to the normalized correlation Rather, it is represented only as a factor of the processing gain that can be the number of independent observations for the given detection threshold [23]. These features are independent of LiDAR signal shapes. Since this SNR degradation is independent on the processing gain GP, we normalized this factor on the results (GP = 19.3 dB was used). We can use a dual-drive MZM for the amplitude modulation, or introduce the true-random signal on the other physical quantities of light
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