Prediction of the Random Error of a Laser Gyroscope Using the Modified GM (1, 1) Model

Fig. 3. Noise coefficient prediction graphs measured by traditional grey prediction algorithm. (a) X-axis measuremental noise coefficient; (b) Y-axis measuremental noise coefficient; (c) Z-axis measuremental noise coefficient

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Fig. 4. Data sequence curves after wavelet filtering

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Fig. 5. Noise coefficient prediction graphs measured improved coefficient. (a) X-axis measuremental noise coefficient; (b) Y-axis measuremental noise coefficient; (c) Z-axis measuremental noise coefficient

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Fig. 6. Random error prediction curves of laser gyroscope. (a) Measuremental noise coefficient; (b) angle random walk coefficient; (c) coefficient of zero deviation instability

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Table 1. Variance ratios of random error prediction by traditional GM (1,1) model
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Table 1. Variance ratios of random error prediction by traditional GM (1,1) model
Coefficient ofrandom error Q N B K R
X-axis variance ratio 0.53 0.52 0.49 0.52 0.56
Y-axis variance ratio 0.50 0.53 0.53 0.53 0.53
Z-axis variance ratio 0.54 0.59 0.59 0.59 0.59

Table 2. Accuracy classification of GM (1,1) model
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Table 2. Accuracy classification of GM (1,1) model
Precision grade 1 2 3 4
C <0.35 <0.5 <0.65 ≥0.65

Table 3. Variance ratios of random error prediction by modified GM (1,1) model
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Table 3. Variance ratios of random error prediction by modified GM (1,1) model
Coefficient ofrandom error Q N B K R
X-axis variance ratio 0.26 0.25 0.27 0.274 0.27
Y-axis variance ratio 0.15 0.28 0.27 0.27 0.27
Z-axis variance ratio 0.16 0.14 0.14 0.14 0.14

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Xiang Li, Lixin Wang, Qiang Sheng. Prediction of the Random Error of a Laser Gyroscope Using the Modified GM (1, 1) Model[J]. Acta Optica Sinica, 2020, 40(12): 1204001

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