Chinese Journal of Lasers, Volume. 45, Issue 11, 1110004(2018)
Waveform Decomposition of Echoes for Airborne Lidar Based on Seeker Optimization Algorithm
Figures & Tables(9)
Fig. 1. Transmitted pulse of airborne lidar described by skewed normal distribution functions
Fig. 3. Processing results of ocean sounding data. (a) Original signal; (b) wavelet filtering; (c) layer-stripping strategy; (d) inflection point method
Fig. 4. Fitting results. (a) Based on Gaussian function; (b) based on skewed normal distribution function
Fig. 5. Six groups of echo signals and their corresponding decomposition results based on Gaussian waveform decomposition algorithm. (a) The first group; (b) the second group; (c) the third group; (d) the fourth group; (e) the fifth group; (f) the sixth group
Fig. 6. Six groups of echo signals and their corrseponding decomposition results based on skewed normal distribution function decomposition algorithm. (a) The first group; (b) the second group; (c) the third group; (d) the fourth group; (e) the fifth group; (f) the sixth group
Table 1. Waveform parameters of echo signals based on Gaussian waveform decomposition algorithm and evaluation indicators
View tableTable 1. Waveform parameters of echo signals based on Gaussian waveform decomposition algorithm and evaluation indicators
Number of echoes Amplitude /mV Mean value Half width Correlation coefficient Root mean square error 1 16235.18 83.60 1.83 2 15362.58 109.90 2.74 3 7270.81 76.87 1.79 4 550.62 117.65 1.94 0.9858 40.72 5 3605.38 143.30 1.69 6 2864.04 125.23 1.67 7 769.15 133.61 1.92 8 673.58 94.32 2.01
Table 2. Waveform parameters of echo signals based on skewed normal distribution function decomposition algorithm and evaluation indicators
View tableTable 2. Waveform parameters of echo signals based on skewed normal distribution function decomposition algorithm and evaluation indicators
Number of echoes Amplitude /mV Mean value Half width Partiality coefficient Correlation coefficient Root mean square error 1 15586.94 84.15 1.91 -0.39 2 14719.58 110.74 2.86 -0.41 3 7099.78 77.08 1.81 -0.16 4 5585.31 117.25 1.96 0.26 5 3708.94 142.83 1.69 0.39 0.9951 22.35 6 2867.92 124.91 1.67 0.24 7 766.97 134.43 1.91 -0.37 8 672.88 94.71 2.04 -0.26
Table 3. Evaluation indicators of echo signals based on Gaussian waveform decomposition and skewed normal istribution function decomposition algorithm
View tableTable 3. Evaluation indicators of echo signals based on Gaussian waveform decomposition and skewed normal istribution function decomposition algorithm
Number of echo signals Correlation coefficient ρ Root mean square error y rmseGaussian waveform decomposition Skewed normal distribution function decomposition Gaussian waveform decomposition Skewed normal distribution function decomposition 1st group 0.9934 0.9985 18.21 9.25 2nd group 0.9875 0.9965 19.56 10.41 3rd group 0.9732 0.9954 56.97 23.64 4th group 0.9922 0.9948 26.86 20.92 5th group 0.9918 0.9948 20.12 16.04 6th group 0.9935 0.9984 28.87 14.99
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Shen Jun, Shang Jianhua, Sun Jiatong, He Yan. Waveform Decomposition of Echoes for Airborne Lidar Based on Seeker Optimization Algorithm[J]. Chinese Journal of Lasers, 2018, 45(11): 1110004
Paper Information
Category: remote sensing and sensor
Received: Apr. 15, 2018
Accepted: --
Published Online: Nov. 15, 2018
The Author Email: Jianhua Shang (jhshang@dhu.edu.cn)
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