Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (4): 950-958.doi: 10.13229/j.cnki.jdxbgxb20211034

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Time delay estimation of linear frequency-modulated continuous-wave lidar signals via SESTH

Xue-mei LI1,2(),Chun-yang WANG1,3(),Xue-lian LIU3,Da XIE1   

  1. 1.School of Electronic and Information Engineering，Changchun University of Science and Technology，Changchun 130022，China
    2.School of Mechanical and Control Engineering，Baicheng Normal University，Baicheng 137000，China
    3.Xi'an Key Laboratory of Active Photoelectric Imaging Detection Technology，Xi'an Technological University，Xi'an 710021，China
  • Received:2021-10-04 Online:2022-04-01 Published:2022-04-20
  • Contact: Chun-yang WANG E-mail:lixuemei556677@163.com;wangchunyang19@163.com

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Abstract:

The parameters extraction of the target echo signal of linear frequency-modulated continuous-wave （LFMCW） lidar is more difficult under low signal-to-noise ratio （SNR）. To solve this problem， a signal time delay estimation method based on synchroextracting S transform based on the Hough transform （SESTH） is proposed. Firstly， integrating Hough transform， the SESTH model of a Chirp signal was constructed. Then， the parameter estimation models of initial frequency and frequency modulation rate of the Chirp signal were derived. Finally， using the time-frequency characteristics of the LFMCW lidar transmitted signal and echo signal， the time delay estimation model of a Chirp signal was constructed， and the relative distance between a target and the lidar was effectively calculated. In order to verify the effectiveness of the algorithm， simulation comparative analysis were carried out. The results show that the minimum relative error value of the proposed SESTH is 3.191×10-6 when the time delay is 4.34 μs； the minimum relative root mean square error value is 0.014 65 in the case of SNR=-6~25?dB， and only 0.0499 s is consumed to execute the target echo signal once.

Key words: signal and information processing, synchroextracting S transform based on the Hough transform, time delay estimation, linear frequency-modulated continuous-wave lidar, Chirp signal

CLC Number: 

  • TN911.7

Fig. 1

Hough transform principle"

Table1

Parameters of Chirp signal x1(t) and x2(t)"

参 数数值参数数值
幅值1扫频周期/μs10
衰减系数1初始频率/GHz1.6
采样频率/GHz64扫频带宽/GHz6
时延/μs0.5

Fig.2

Time-frequency representation of transformations without noise"

Fig.3

Time-frequency representation of transformations with SNR=5?dB"

Table 2

Rényi entropy evaluation results without noise"

变 换Rényi 熵值变 换Rényi 熵值
STFT0.4260GST0.5222
ST0.5052WVD1.8471
SET0.0795HHT0.3595
SEST0.0341

Table 3

Rényi entropy evaluation results with SNR=5?dB"

变 换Rényi 熵值变 换Rényi 熵值
STFT1.2442GST1.4071
ST1.3374WVD2.6882
SET1.2287HHT1.1817
SEST0.2528

Fig.4

Peak search of various transforms"

Fig.5

Relative error curve of time delay estimation of SESTH"

Fig.6

Relative root mean square error curve of time delay estimation accuracy of Chirp signal"

Table 4

Running time comparison of algorithms"

变 换运行时间/s变 换运行时间/s
STFTH93.1186WVDH1.1813
STH41.6180HHTH0.8467
GSTH32.2572SESTH0.0681
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