Design and hardware implementation of modified Rife algorithm for FMCW LiDAR

被引:0
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作者
Ye M. [1 ,2 ]
Liu H. [1 ,2 ]
Zhao Y. [1 ]
Sun Z. [1 ,2 ]
Hu B. [1 ,2 ]
机构
[1] School of Microelectronics, Tianjin University, Tianjin
[2] Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, Tianjin
关键词
FMCW LiDAR; FPGA; frequency estimation; modified Rife algorithm;
D O I
10.3788/IRLA20220222
中图分类号
学科分类号
摘要
FMCW LiDAR is being widely studied for its high accuracy, strong anti-interference capability and simultaneous ranging and speed measurement. The inherent fence effect of FFT will introduce errors in ranging and speed measurement. To solve this problem, firstly, this paper analyzes the law of spectrum amplitude and phase angle, and then combines with the principle of sine function, proposes a modified Rife algorithm that is easy to implement in hardware. When the estimated frequency is close to the FFT quantization frequency point, this method can effectively reduce the error of the Rife algorithm. The simulation and FPGA verification results show that when the SNR is −10 dB, the mean error (ME) and root mean square error (RMSE) of the algorithm are reduced by 69.6% and 50.7%, respectively, compared with the traditional Rife algorithm. The calculation amount is only increased by two multiplications and additions, which is negligible compared to N-point FFT computation. Finally, in order to verify the effectiveness of the algorithm, this paper build an optical test platform to simulate the intermediate frequency echo signal of LiDAR. The results show that the algorithm can achieve simultaneous ranging and speed measurement within 112 m. The ranging error is no more than 5 cm, and the speed measurement error is no more than 0.16 km/h. The algorithm meets the demand of real-time ranging and speed measurement. © 2022 Chinese Society of Astronautics. All rights reserved.
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  • [1] Wu Xiru, Xue Qiwei, 3D vehicle detection for unmanned driving system based on LiDAR, Optics and Precision Engineering, 30, 4, pp. 489-497, (2022)
  • [2] Wei Yu, Jiang Shilei, Sun Guobin, Et al., Design of solid-state array laser radar receiving optical system, Chinese Optics, 13, 3, pp. 517-526, (2020)
  • [3] Ahmod Z, Liao Y M, Kuo S I, Et al., High-power and high-responsivity avalanche photodiodes for self-heterodyne FMCW LiDAR system applications, IEEE Access, 9, pp. 85661-85671, (2021)
  • [4] Wang C S, Zhang Y S, Zheng J L, Et al., Frequency modulated continuous wave dual frequency LiDAR based on a monolithic integrated two-section DFB laser, Chinese Optics Letters, 19, 11, (2021)
  • [5] Gao Li, Zhang Xiaoli, Ma Jingting, Et al., Quantum enhanced doppler LiDAR based on integrated quantum squeezed light source (Invited), Infrared and Laser Engineering, 50, 3, (2021)
  • [6] Chen Peng, Zhao Jiguang, Song Yishuo, Et al., Comparison on detection performance of FMCW and pulsed LiDAR in aerosol environment, Infrared and Laser Engineering, 49, 6, (2020)
  • [7] Qu Xinghua, Zhi Guangtao, Zhang Fumin, Et al., Improvement of resolution of frequency modulated continuous wave laser ranging system by signal splicing, Optics and Precision Engineering, 23, 1, pp. 40-47, (2015)
  • [8] Zhou Yongsheng, Ma Xunpeng, Zhao Yiming, Et al., Frequency estimation of the weak signal of the coherent wind LiDAR, Infrared and Laser Engineering, 47, 3, (2018)
  • [9] Zou Lirong, Zhu Li, Zhang Sheng, Et al., LFMCW radar moving target ranging method based on improved rife algorithm, Journal of Microwaves, 35, pp. 233-238, (2019)
  • [10] Sun Hongjun, Wang Xiaowei, Modified rife algorithm for frequency estimation of sinusoid wave based on amplitude and phase criterion, Journal of Tianjin University (Science and Technology), 51, 8, pp. 810-816, (2018)