• Optics and Precision Engineering
  • Vol. 31, Issue 24, 3549 (2023)
Lirong ZHAO1, Guangfu YUAN2,*, Dong WU1, Qun GAO1, and Xiaoxun WANG1
Author Affiliations
  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences; Changchun30033, China
  • 2Unit 95859 of PLA, Jiuquan735000, China
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    DOI: 10.37188/OPE.20233124.3549 Cite this Article
    Lirong ZHAO, Guangfu YUAN, Dong WU, Qun GAO, Xiaoxun WANG. Real-time solution of optimal uniform approximation polynomial velocity for theodolite[J]. Optics and Precision Engineering, 2023, 31(24): 3549 Copy Citation Text show less

    Abstract

    The use of a theodolite for real-time velocity calculation has always been a challenge in the field of measurement and control. To improve the real time and high accuracy of theodolite solutions, the laser ranging optoelectronic theodolite project has proposed an optimal uniform approximation polynomial velocity solution method through repeated experiments, which ensures both real-time and accurate velocity. First, a single station theodolite and laser ranging are used to obtain the spatial position of the target, and an improved least squares method is used to fit and filter distance measured by the laser. Then, by solving the velocity model, the initial velocity value is calculated. When using polynomials to approximate the true value of velocity, using conventional expressions can result in significant computational errors. To reduce computational errors, polynomials are combined with cubic Chebyshev polynomials to obtain the optimal uniform approximation polynomial for calculating the velocity function. The optimal uniform approximation polynomial velocity function uses the cubic finite difference method to identify the velocity outliers and obtain real-time and high-precision target velocity values. The indicators of laser-ranging theodolite speed measurement include real time ability (delay<100 ms) and accuracy (error<1 m/s). The speed measurement value of GPS loaded on the UAV is taken as the true value, and multiple algorithms are used to calculate the target speed. The test results show that the Gaussian function method for speed calculation has good real-time performance; however, the speed measurement accuracy is >1.5 m/s. The Kalman method has good accuracy in calculating velocity; however, owing to the use of a large amount of historical data, the velocity value lags behind. The speed calculated by the optimal uniform approximation polynomial method in this study has good real-time performance and a delay of 50 ms. The mean square deviation of speed accuracy is 0.8 m/s, which meets the equipment’s indicator requirements.
    xc=xo+R×cos Acos Eyc=yo+R×sin Ezc=z0+R×sin Acos E(1)

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    Y1=f1(X1,X2,,Xt)Y2=f2(X1,X2,,Xt)Yn=fn(X1,X2,,Xt)(2)

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    y1=f1(x1,x2,,xt)y2=f2(x1,x2,,xt)yn=fn(x1,x2,,xt)(3)

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    v1=l1-y1v2=l2-y2vn=ln-yn(4)

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    v1=l1-f1(x1,x2,xt)v2=l2-f2(x1,x2,xt)vn=ln-fn(x1,x2,xt)(5)

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    P=1e-(δ12/σ12+δ22/σ22++δn2/σn2)/2dδ1dδ2dδnσ1σ2σn(2π)(6)

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    δ12σ12+δ22σ22++δn2σn2=min(7)

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    ν12σ12+ν22σ22++νn2σn2=min(8)

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    Y1=a11X1+a12X2++a1tXtY2=a21X1+a22X2++a2tXtYn=an1X1+an2X2++antXt(9)

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    y1=a11x1+a12x2++a1txty2=a21x1+a22x2++a2txtyn=an1x1+an2x2++antxt(10)

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    v1=l1-(a11x1+a12x2++a1txt)v2=l2-(a21x1+a22x2++a2txt)vn=ln-(an1x1+an2x2++antxt)(11)

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    P1P2=R12+R22-2R1R2(cos(A1-A2)cosE1cosE2+sinE1sinE2)(12)

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    v=R12+R22-2R1R2(cos(A1-A2)cosE1cosE2+sinE1sinE2)t2-t1(13)

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    Δv=vR1δ(R1)+vR2δ(R2)+vA1δ(A1)+vA2δ(A2)+vE1δ(E1)+vE2δ(E2),(14)

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    vR1=R1-R2(cos(A1-A2)cosE1cosE2+sinE1sinE2)(t2-t1)2v(15)

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    vR2=R2-R1(cos(A1-A2)cosE1cosE2+sinE1sinE2)(t2-t1)2v(16)

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    vA1=R1R2(sin(A1-A2)cosE1cosE2)(t2-t1)2v(17)

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    vA2=R1R2(sin(A2-A1)cosE1cosE2)(t2-t1)2v(18)

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    vE2=R1R2(cos(A1-A2)cosE1sinE2-sinE1cosE2)(t2-t1)2v(19)

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    vE1=R1R2(cos(A1-A2)sinE1cosE2-cosE1sinE2)(t2-t1)2v(20)

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    T0(x)=1(15)

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    T1(x)=x(16)

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    Tn+1(x)=2xTn(x)-Tn-1(x)(17)

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    T2x=2x2-1(18)

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    T3x=4x3-3x(19)

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    fxi-Qnxi=α(-1)if-Qn(20)

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    f(x)~j=0djTj(x)(21)

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    j=0ndjTj(x)(22)

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    fx=j=0ajxj(23)

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    fxPnx=j=0najxj(24)

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    Pnx=j=0ndjTj(x)(25)

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    Qmx=j=0mdjTj(x)(26)

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    EmQm+1=Qm+1-Qm=dm+1(27)

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    fx-Pm(x)maxfx-Pnx+j=m+1ndj(28)

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    D0=d0-d2/2(29)

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    Dj=(dj-dj+2)/2(30)

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    Dn-1=dn-1/2(31)

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    vn=dn/2(32)

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    Pnx=vn-2+vn-3++v0(33)

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    v=d3+(v3+v2+v1+v0)(34)

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    v3=d3/2(41)

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    v2=2xv3+d2/2(42)

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    v1=2xv2-v3+(d1-d3)/2(43)

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    v0=2xv1-v2+(d0-d2/2)(44)

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    Δmfi=j=0m(-1)jCmjfi+m-j(35)

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    2fi=fi+2-2fi+1+fi(36)

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    3fi=fi+3-3fi+2+3fi+1-fi(37)

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    4fi=fi+4-4fi+3+6fi+2-4fi+1+fi(38)

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    fxi;;xi+m=fi+m/2mhmm!(39)

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    mfi=hmfm(ζ)(40)

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    Lirong ZHAO, Guangfu YUAN, Dong WU, Qun GAO, Xiaoxun WANG. Real-time solution of optimal uniform approximation polynomial velocity for theodolite[J]. Optics and Precision Engineering, 2023, 31(24): 3549
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