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FMCW lidar multitarget detection based on skeleton tree waveform matching

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Abstract

Frequency-modulated continuous-wave lidar realizes 4D (three-dimensional space and velocity) imaging of the scene by emitting positive and negative frequency sweep laser signals. The premise of it is to identify the frequency points corresponding to the same target in the positive and negative sweep echo signals. For dechirp receiving, there is usually one peak in the frequency spectrum of the positive and negative sweep signals, respectively. Therefore, it is easy to identify and match the peaks. But in a complex environment, the laser beam will irradiate multiple targets at the same time. In addition, beam scanning and target motion cause the echo spectrum to broaden. The above reasons make it extremely difficult to identify and match peaks in practice. To solve this problem, the waveform-matching algorithm based on the skeleton tree is first applied to multitarget echo pairing. The basic idea of the algorithm is to quantify the target echo hierarchically to generate a skeleton tree. The generation of nodes is based on the relative amplitude of waveform peaks and reflects the characteristics of wave crests nesting. Then the similarity of the signal is determined by comparing the distance between the two signal waveform feature trees. Finally, the waveforms are matched in terms of similarity. To further substantiate the role of the proposed algorithm, imaging experiments and related comparative data for different targets have been completed. The results show that the accuracy of matching processed by the algorithm exceeds 90%, which is improved by about 50% compared with not using the algorithm for the target whose overlapping part accounts for a large proportion of itself.

© 2021 Optical Society of America

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