CN105973210B - Species mapper sole position estimation filters - Google Patents

Species mapper sole position estimation filters Download PDF

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CN105973210B
CN105973210B CN201610334404.3A CN201610334404A CN105973210B CN 105973210 B CN105973210 B CN 105973210B CN 201610334404 A CN201610334404 A CN 201610334404A CN 105973210 B CN105973210 B CN 105973210B
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mapper
position
tk
sole
support
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CN105973210A (en
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杭义军
邢丽
贾文峰
吕印新
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极翼机器人(上海)有限公司
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Abstract

本发明涉及测绘设备领域,尤其涉及种测绘仪杆底位置滤波估计方法。 The present invention relates to the field of surveying and mapping apparatus, and particularly to the bottom position estimation filter types mapper rod. 本发明公开设计的种测绘仪杆底位置滤波估计方法,先将测绘仪的支撑杆围绕待测点倾斜旋转若干圈自身倾斜若干获取旋转过程中多个位置点的位置坐标,然后测量测绘仪支撑杆的杆长,通过拓展卡尔曼滤波算法滤波估计求得测绘仪支撑杆的杆底位置坐标,这样不仅可以解决地磁变化和磁场干扰对测绘仪倾斜量修正精度的影响,同时缩减了生产成本、减小了测绘仪杆底位置修正模块的体积及重量、提高了测绘仪杆底位置的估计精度、简化了估计测绘仪杆底位置的操作修正过程。 Bottom position estimation filter types mapper rod design of the present invention disclosed, a plurality of inclined positions of several points acquired during rotation of the rotating ring position coordinates of a plurality of first inclined support rod mapper itself around the site to be tested, and then measuring mapper support rod length rod, the estimated position coordinates determined sole mapper support bar by expanding Kalman filter algorithm, which can solve not only the effect on the amount of tilt correction accuracy mapper geomagnetic variations and magnetic interference, while reducing the cost of production, reducing the volume and weight of the position correction sole mapper module improve the estimation accuracy mapper sole position, simplifying the operation process of correcting the estimated position of the sole mapper.

Description

一种测绘仪杆底位置滤波估计方法 Position estimating method, a substrate mapper filter rod

技术领域 FIELD

[0001] 本发明涉及测绘设备领域,尤其涉及一种测绘仪杆底位置滤波估计方法。 [0001] The present invention relates to the field of surveying and mapping apparatus, and particularly to a method for estimating the end position of the filter rod mapper.

背景技术 Background technique

[0002] 传统的测绘仪每次测量需要调节测量杆垂直,测量耗时大,测量效率低,且一般气泡调零的精度与操作人员的细心程度和技术相关,且当测量员长时间高强度测量时,由于测量员的重复操作与疲劳很容易出现调平不准,使得测量精度严重下降,从而影响工程施工的精度,造成人力与物力的严重浪费。 [0002] Traditional mapper needs to be adjusted each measurement the measuring rod vertically, consuming large measure, the measurement efficiency is low, and the degree of care and skill and precision of the operator typically bubbles zero correlation, and high strength for a long time when the surveyor when measured, due to the surveyor's repeated operations and is prone to fatigue leveling are not allowed, so that the measurement accuracy of a serious decline, thus affecting the accuracy of construction, resulting in a serious waste of human and material resources.

[0003] 因此,随着MEMS倾角测量技术的发展与应用,近些年国内外的各大测绘仪生产公司纷纷推出了带有倾斜测量补偿的测绘仪产品,从而将测绘人员从重复的调平操作中解放了出来,其主要特点是允许测绘员在使用测绘仪测量时,不需要调平的情况下依然能够提供等效于精确调平后的打点测量精度,在有效提高测绘效率和测绘精度的同时,提高了测绘数据的一致性,减小了人为调平引入的各种不可控制的误差。 [0003] Therefore, with the development and application of MEMS tilt measurement technology at home and abroad in recent years major mapping instrument manufacturing companies have launched leveling tilt measurement with compensation of mapping instrument products, so surveyors from repeated in the case where the operation liberated, its main features is to allow surveyor measured when using mapping does not require leveling still possible to provide the striking measurement accuracy equivalent to the precise leveling, the mapping effectively improve the efficiency and accuracy of mapping at the same time, improved mapping data consistency, reduces uncontrolled various errors artificially introduced leveling.

[0004] 但是现有使用的倾斜测量模块由于会使用MEMS传感器解算输出的水平倾角和航向角信息,这些角度信息的精度会受到MEMS传感器性能的影响,造成测绘仪杆底位置的估计精度下降,同时,原有测绘仪倾斜改正方法中使用的高性能的工业级MEMS传感器,价格贵、成本高、体积大。 [0004] However, the conventional tilt measurement module used in the MEMS sensor due to the use horizontal angle resolver output and the heading angle information, angle information accuracy of these MEMS sensor performance will be affected, resulting in the estimation accuracy of the sole mapper lowered position Meanwhile, high-powered MEMS sensor mapper original tilt correction used in the method, expensive, high cost, large volume. 因此,从减小生产成本、缩小模块体积,以及提高测绘仪杆底位置估计精度的目的出发,提出了一种基于拓展卡尔曼滤波的新型测绘仪杆底位置滤波估计方法。 Therefore, to reduce the production costs, reduce the volume of the module, and the sole purpose of improving mapper starting position estimation accuracy, a method is proposed to expand the bottom position estimation Kalman filter mapper novel method based on the lever.

发明内容 SUMMARY

[0005] 本发明的目的是提供一种测绘仪杆底位置滤波估计方法,鉴于上述问题,它弥补了上述的缺陷并提供以下优点: [0005] The object of the present invention is to provide a sole position estimation filter mapper, in view of the above problems, which make up the above-mentioned drawbacks and provides the following advantages:

[0006] —种测绘仪杆底位置滤波估计方法,其中,所述方法包括: [0006] - the position of the sole species mapper filter estimation method, wherein the method comprises:

[0007] 将测绘仪的支撑杆的底端安放在待测点; [0007] The bottom end of the support bar mapper is placed at the point to be measured;

[0008] 将所述测绘仪的支撑杆围绕所述待测点倾斜旋转若干圈,记录所述测绘仪旋转过程中多个位置点的位置坐标; [0008] The rotation of the inclined supporting rod mapper several turns around the test point, position coordinates of a plurality of recording the location of the point mapper during rotation;

[0009] 测量所述测绘仪支撑杆长度I0; [0009] measuring the length I0 mapper support rod;

[0010] 利用所述测绘仪的支撑杆长度和所述测绘仪旋转过程中的多个位置点的位置坐标通过拓展卡尔曼滤波算法对测绘仪的杆底位置及支撑杆杆长误差进行滤波估计,以计算出所述测绘仪的杆底位置坐标。 [0010] plurality of position coordinate points using the position of the support rod length of the mapper and mapper during rotation of the expanding Kalman filter algorithm and the position of the sole support of the club length mapper error estimate by filtering , mapping to calculate the position coordinates of the sole instrument.

[0011] 上述的方法,其中,所述方法包括: [0011] The above method, wherein the method comprises:

[0012] 所述测绘仪的支撑杆围绕所述支撑杆底端以8字型或圆形方式倾斜旋转。 [0012] The mapper support bars around the bottom end of the support bar in a 8-shaped or circular rotation inclined.

[0013] 上述的方法,其中,所述方法还包括: [0013] The above method, wherein the method further comprises:

[0014] 将所述测绘仪的支撑杆倾斜旋转过程中的采集的位置坐标存储至所述测绘仪的存储单元中; [0014] The mapper support bars inclined position coordinate acquired during rotation of the storage unit to the storage in mapper;

[0015] 输入所述测绘仪的支撑杆杆长,并于所述测绘仪的微型处理器中通过拓展卡尔曼滤波算法对所述测绘仪的支撑杆长度和存储在所述存储单元中的位置坐标进行滤波估计。 [0015] The input of the mapper support club length, and the mapper to the microprocessor through the support rod length and storing the mapper expansion Kalman filter position in the storage unit coordinates filter estimation.

[0016] 上述的方法,其中,所述方法包括: [0016] The above method, wherein the method comprises:

[0017] 通过拓展卡尔曼滤波估计算法对所述测绘仪的支撑杆杆底位置坐标[X,y,z]及支撑杆的杆长误差A 1〇进行估计计算,根据拓展卡尔曼状态方程Xk = FX1^1和量测方程 [0017] The calculation estimating the position of the bottom support club mapper coordinates [X, y, z] and the support rod by rod length error A 1〇 expanding Kalman filter estimation algorithm, according to the equation Xk expanded state Kalman = FX1 ^ 1 and the measurement equation

Figure CN105973210BD00051

计算得出; Calculated;

[0018] 其中F为单位矩阵,Xk-Atk-i时刻的状态量X,Xk为tk时刻的状态量,状态量X= [X, y,z,△ 10],包含支撑杆杆底位置坐标[X,y,z]及支撑杆的杆长误差△ Io; Z为观测量,选取支撑杆长度Ic1为观测量,[X1,y1,Z1]为所述存储单元中的第i个点位置坐标α多1)。 [0018] where F is the unit matrix state, Xk-Atk-i in time an amount X, Xk is the state quantity at tk, the state quantity X = [X, y, z, △ 10], comprising a support bottom club position coordinates [X, y, z] and strut lever length error △ Io; Z is observations, Ic1 selected length of the support rods observations, [X1, y1, Z1] is the i-th position of the storage unit multi-coordinate α 1).

[0019] 上述的方法,其中,所述方法还包括: [0019] The above method, wherein the method further comprises:

[0020] 按照 [0020] According to

Figure CN105973210BD00052

Figure CN105973210BD00053

五个迭代更新方程,通过拓展卡尔曼滤波方法估计状态量; Five iterative update equation, by expanding the amount of estimated state Kalman filter method;

[0021] 其中,为tk时刻状态量的一步预测值,为^寸刻状态量的估计值,K为tk时刻的滤波增益矩阵,I为tk时刻均方误差矩阵的一步预测值,时刻均方误差矩阵的估计值,$为tk时刻均方误差矩阵的估计值,Hk为量测方程一阶线性化后的量测矩阵, /z ('丨为状态量A对应的量测方程,上标T表不矩阵的转置,Rk为tk时刻量测噪声,Qk为tk时刻状态噪声阵。 [0021] wherein in one step the predicted value at tk state quantities, the estimated value ^ inch engraved state quantities, K is a filter gain matrix tk time, I is at tk mean square error step prediction value matrix, moments mean square estimation error matrix, $ is at tk mean square error estimate matrix Hk for the measurement equation first order linearized measurement matrix, / z ( 'Shu for the measurement equation state quantity a corresponding superscript table T are not transposed matrix, Rk is the measurement noise at tk, Qk is noise at tk state array.

[0022] 上述的方法,其中,所述方法还包括: [0022] The above method, wherein the method further comprises:

[0023] 将估计得到的杆底位置直角坐标[x,y,z]和杆长误差Δ 1〇代入 [0023] The estimated position of the sole obtained Cartesian coordinates [x, y, z] and the lever length error Δ 1〇 substituting

Figure CN105973210BD00054

式中,即可得到测绘仪杆底位置的经炜高估计值[λ,L,h]; In the formula, to obtain a sole mapper high position estimate by Wei [λ, L, h];

[0024] 其中,r为地球半径,λ1 ,L1A1分别表示所述存储单元中存储的第一个点的经度、炜度和高度。 [0024] wherein, r is the radius of the earth, λ1, L1A1 represent a longitude of the first point stored in the storage unit, Wei and height.

[0025] 综上所述,本发明公开设计的一种测绘仪杆底位置滤波估计方法,通过将测绘仪的支撑杆围绕待测点倾斜旋转若干圈获取旋转过程中多个位置点的位置坐标,结合测量的测绘仪支撑杆的杆长,采用拓展卡尔曼滤波算法滤波估计求得测绘仪支撑杆的杆底位置坐标,这样不仅可以解决地磁变化和磁场干扰对测绘仪倾斜量修正精度的影响,同时缩减了生产成本、减小了测绘仪杆底位置修正模块的体积及重量、提高了测绘仪杆底位置的估计精度、简化了估计测绘仪杆底位置的操作修正过程。 [0025] In summary, a method for estimating the end position of the filter rod mapper design disclosed in the present invention, obtaining position coordinates of points of a plurality of positions during rotation of the support rod by the mapper tilt about the point of rotation to be measured a number of turns combining the measured stem length of the support rods mapper using Kalman filter algorithm Development estimated position coordinates determined mapper sole support rods, which can not only solve the geomagnetic variations and influence of magnetic interference mapping tilt amount correction accuracy of the meter while reducing the production cost, reducing the size and weight of the position correction sole mapper module improve the estimation accuracy mapper sole position, simplifying the operation process of correcting the estimated position of the sole mapper.

附图说明 BRIEF DESCRIPTION

[0026] 参考所附附图,以更加充分的描述本发明的实施例。 [0026] reference to the appended drawings, a more full description of the embodiments of the present invention. 然而,所附附图仅用于说明和阐述,并不构成对本发明范围的限制。 However, the accompanying drawings and set forth for illustration only and do not limit the scope of the present invention.

[0027] 图1是本发明的流程图。 [0027] FIG. 1 is a flowchart illustrating the present invention.

[0028] 图2是本发明的测绘仪的支撑杆倾斜旋转示意图。 [0028] FIG. 2 is a schematic view of the rotary mapper inclined supporting rod of the present invention.

具体实施方式 Detailed ways

[0029] 下面结合附图和具体的实施例对本发明作进一步的说明,但是不作为本发明的限定。 [0029] The drawings and the following embodiments in conjunction with specific embodiments of the present invention will be further described, but not limitative of the present invention.

[0030] 目前的测绘仪的主要工作原理就是在测绘仪内部安装一个低成本的倾角测量模块,通过倾角测量模块实时测量倾斜角和航向角,结合倾斜后的经炜高,利用精确的算法补偿修正方法,改正倾斜导致的测量误差,获得精确的打点经炜高测量参数。 [0030] The operating principle of the present mapper mapper is mounted inside a low-cost tilt measurement module, the tilt measurement module in real time by measuring the heading angle and the tilt angle, the tilt by the combination of high Wei, using accurate compensation algorithm correction means to correct the measurement error due to the inclination, to obtain high accurate dot Wei was measured parameters. 但该误差改正算法精度与航向角的测量精度直接相关,而由于低成本倾角测量模块,一般使用地磁传感器获取航向信息,而地磁传感器的测量原理主要依赖于微弱的地磁场信息,所以该航向角的精度很容易受测绘仪内部的线圈、铁磁物质,以及测绘仪周边的矿场分布、钢铁建筑、设备的影响,所以一般的使用精度不是很理想。 However, the error correction algorithm is directly related to the accuracy of the measurement accuracy of the heading angle, the tilt measurement module for low cost, using the general heading information acquiring geomagnetic sensor, the geomagnetic sensor and the measuring principle depends on the weak geomagnetism information, the heading angle the accuracy is susceptible to internal coil mapping instrument, a ferromagnetic substance, and the periphery of the mine mapper distribution, steel buildings, equipment, it is generally not very desirable to use precision.

[0031] 虽然,所有倾角计模块都会针对这些地磁干扰以及磁传感器的误差进行校准或者误差补偿研究,但由于地磁相对微弱,且磁干扰形式复杂、干扰源众多、对环境依赖性强,即使是先进的校准算法加上严格的校准流程,也很难保证磁航向的测量精度在所有使用情况下都能满足倾斜改正测量的应用需求,一般在充分标定的情况下,磁航向角精度也很难达至IJl度以下的精度。 [0031] Although the modules are all inclinometer calibration or compensation of the geomagnetic interference and errors for those errors of the magnetic sensor, but is relatively weak geomagnetism, and magnetic interference in the form of a complex, many sources of interference, a strong dependence on the environment, even advanced calibration algorithms coupled with strict calibration procedure, it is difficult to ensure accuracy magnetic heading of the application can meet the needs of measurements of tilt correction in all use cases, generally in the case of full calibration, magnetic heading angle accuracy is difficult IJl degrees or less to achieve accuracy.

[0032] 另外,由于补偿算法中用到的航向是真航向而非磁航向,因此,我们需要对测量到的磁航向进行修正,其中磁偏角的获取一般通过如下两类方法获得: [0032] Further, since the compensation algorithm is used in the course not true heading magnetic heading, therefore, we need to measure the magnetic heading correction, which acquires magnetic declination is generally obtained by two methods:

[0033] 方法一、通过当地经炜高利用地磁偏角模型查询。 [0033] The method, by using a high local magnetic declination by Wei model query.

[0034] 方法二、传统四位置或八位置罗差修正方法获得。 [0034] Method II, conventional four or eight-position position correcting method for obtaining a difference Lo.

[0035] 其中,方法一的特点是使用方便,只需要在程序中固化一个不太复杂的地磁模型, 但由于精确的地磁数据库巨大,且更新困难,因此,一般固化使用的地磁偏角模型都较为粗略,无法反映细小区域的细微变化,其精度也只能勉强达到1度左右,且随着时间的推移,地球磁场也在发生着变化,如无法及时更新数据库,误差也会更大。 [0035] wherein the method is characterized by ease of use, only a less complicated curing geomagnetic model in the program, but because of the great precision of geomagnetism database, and difficult to update, therefore, the use of magnetic declination models generally are cured more rough, do not reflect subtle changes in a small area, and its accuracy could barely reach 1 degree, and over time, the Earth's magnetic field is changing, if you can not update the database, the error will be greater. 因此,利用此方法补偿地磁航向获得的航向角精度一般在全航向测量范围内只能达到2度左右的使用精度,且很难进一步提尚。 Thus, the accuracy of the heading angle compensation geomagnetic heading by this method is generally obtained in the whole range heading measurement accuracy using only reach about 2 degrees, and it is difficult to mention still further.

[0036] 方法二一般利用RTK接收的精确位置测量特性,进行多位置差分,获得精确的航向参考,计算多个角度的航向偏差,可以获得较高的真航向参考,一般RTK精度在2cm,水平基线在Im左右,可以获得0.5度航向的精确参考,同时可以修正磁标定后的磁场畸变残差,提高航向角在全范围的精度和误差均匀性,但该方法标定过程复杂,一般需要熟练的技术人员利用半小时左右才能操作完成。 [0036] General Method II using RTK received precise position measurement characteristics, multi-position difference, to obtain an accurate reference heading, course deviation calculated plurality of angles can be obtained a high true heading reference, the general accuracy RTK 2cm, horizontal baseline about Im, precision reference 0.5 degrees heading can be obtained, while the magnetic field can be corrected residual distortion calibration, and to improve the accuracy of the heading angle error in the uniformity of the whole range, but the method is complicated calibration procedure, generally requires a skilled art using about half an hour to complete. 且其标定精度也与操作人员的细心和耐心存在很大的关系,因此,实际航向测量精度一般在1度左右。 Calibration accuracy and which are also significant relationship with care and patience of the operator, and therefore, the actual heading measurement accuracy is generally about 1 degree.

[0037] 因此,为了消除由于磁航向测量不准或易受干扰导致的测绘仪位置修正误差,需要采用一定的改进方式来消除航向测量误差,达到在不使用磁航向测量信息的条件下,实现测绘仪位置修正的目的。 [0037] Accordingly, in order to eliminate errors due to the position correction mapper magnetic heading of the inaccuracy caused by or susceptible to interference, we need a way to eliminate some improvement heading measurement errors, achieve without the use of measured information in a magnetic heading, to achieve mapper position correction purposes. 本发明设计了一种测绘仪杆底位置滤波估计的方法。 The present invention contemplates a method of filtering the position of the sole mapper estimation.

[0038] 如图1所示,首先将测绘仪倾斜旋转若干圈,但是测绘仪是固定在测绘仪支撑杆的一端的,测绘仪支撑杆的另一端固定在待测点上,本申请中于待测点上设置一固定装置,测绘仪支撑杆的另一端通过旋转装置与固定装置连接,这样就可以将测绘仪的支撑杆以一端为固定点进行倾斜旋转。 [0038] As shown in FIG. 1, a plurality of first mapper revolution of inclination, but mapper is fixed to one end of the support rod mapper, mapper other end is fixed on the support rod site to be tested, in the present application a fixing means provided on the point to be measured, and the other end connected to the support rod mapper fixing means by rotation means, so that the mapper can end support bar is inclined to a fixed rotation point. 在倾斜旋转过程中,测绘仪自动记录每次倾斜旋转后的位置坐标, 另外外部再量测测绘仪的支撑杆的长度,因为支撑杆的一端是固定的,这样在倾斜旋转过程中记录测绘仪所处的位置坐标,然后采用拓展卡尔曼滤波算法,结合这些位置坐标和测绘仪支撑杆杆长,滤波估计出测绘仪支撑杆的杆底位置坐标。 In the tilt rotation, the mapper automatically record each position coordinate after the rotation is inclined, then additional external measurement of the length of the support bar mapper because the supporting rod is fixed at one end, so that the recording mapper inclination during rotation in which the position coordinates, and then to expand the use of Kalman filter, and a combination of these position coordinates mapper support club length, filtering the estimated position coordinates mapper sole support bar.

[0039] 实施例一: [0039] Example a:

[0040] ⑴事先测量测绘仪支撑杆长度1〇。 [0040] ⑴ previously measured length of the support bar 1〇 mapper.

[0041] (2)将测绘仪的支撑杆底端安放在待测点,本申请中待测点上设置一个固定装置, 测绘仪支撑杆底端则通过一个旋转装置与固定装置连接,保证支撑杆在围绕底端倾斜画圈旋转时,杆底位置固定不动。 [0041] (2) the bottom end of the support bar is placed in the mapper site to be tested, the present application a fixture is provided on the point to be measured, the bottom end of the support rod mapper connected to the fixing means by a rotating means, to ensure the support when the tilt lever circle rotated about a bottom end, a sole stationary position.

[0042] (3)将测绘仪的支撑杆底端固定后,如图2所示,将支撑杆底端以8字型或圆形或螺旋型进行倾斜画圈旋转; After the bottom [0042] (3) the fixed support bars mapper shown in Figure 2, the bottom end of the support bar 8 in circular or spiral-shaped or circle tilt rotation;

[0043] (4)在倾斜画圈旋转过程中,测绘仪自动记录时间段(t^U)中相等时间间隔的测绘仪多个位置点的位置坐标[λ(1),L(1),h(1)]〜[λ(η),L(n),h(n)],其中λ表示经度、L表示炜度、 h表示高度,该位置是支撑杆上安装有位置测量模块和微型中央处理器的一端,如图2中所示的位置A。 [0043] (4) inclined circle during rotation, a plurality of position coordinates mapper mapper location of the point in time (t ^ U) is equal to the time interval [λ (1), L (1) automatically records, h (1)] ~ [λ (η), L (n), h (n)], where [lambda] represents the longitude, L represents a degree Wei, h represents the height, this position is mounted on the support rod position measuring module and miniature One end of the central processor, the position shown in Figure 2 A.

[0044] (5)在测绘仪的存储单元中读取记录的位置坐标数组[λ«,LW,h«]〜[λω,LW, h(n)],于测绘仪的微型处理器中进行卡尔曼滤波估计,首先是选择其中某一位置为直角坐标系原点,将所有位置的经炜高坐标转换为直角坐标。 [0044] (5) reads information recorded in the storage unit mapper in the array coordinate position [λ «, LW, h«] ~ [λω, LW, h (n)], within mapper micro processor Kalman filter estimation, first select a location for the origin of the rectangular coordinate system, the coordinates of all the high-Wei converts the rectangular coordinate position. 实施例中选择第一个位置坐标点为坐标原点[0,0,0],其余位置坐标转换为直角坐标的过程如式(1)所示,其中r为地球半径。 Select the first embodiment, the position coordinate point to the coordinate origin embodiment [0,0,0], rest position coordinates to Cartesian coordinates as the process of formula (1), where r is the radius of the earth. 转换后的位置坐标数组为[0,0,0],[X (2),y (2),Z⑵]〜[X ω,y ω,Z ω ]。 The position coordinates of the array is converted to [0,0,0], [X (2), y (2), Z⑵] ~ [X ω, y ω, Z ω].

[0045] [0045]

Figure CN105973210BD00071

(1) (1)

[0046] (6)基于转换得到的各个位置点的直角坐标,构建滤波估计方程。 [0046] (6) the position of the respective rectangular coordinate points obtained based on the conversion, the filter constructed estimation equation. 其中滤波估计方程中状态量设为X= [x,y,z,△ 10],其中[x,y,z]为待估计的杆底直角坐标,△ Io为杆长误差估计值;量测量选取为杆长测量值Z = l。 Wherein the filtering is set to the state quantity estimation equation X = [x, y, z, △ 10], where [x, y, z] is estimated to be the sole Cartesian coordinates, △ Io error estimate for the stem length; measurement select a rod length measurement Z = l. . 构建的状态方程和量测方程如式⑵和⑶所示。 Construction of the state equation and the measurement equation and formula ⑵ ⑶ FIG.

[0047] Xk=FXk-I (2) [0047] Xk = FXk-I (2)

[0048] [0048]

Figure CN105973210BD00072

(3) (3)

[0049] 其中F为单位矩阵,Xk-Atk-!时刻的状态量X,Xk为tk时刻的状态量,状态量X= [X, y,z,△ 10]包含支撑杆杆底位置坐标[X,y,z]及支撑杆的杆长误差△ Io; Z为观测量,选取支撑杆长度1〇为观测量,[X1,y1,Z1]为所述存储单元中的第i个点位置坐标(i多1)。 [0049] where F is the unit matrix, Xk-Atk-! Time state quantity X, Xk is the state quantity at tk, the state quantity X = [X, y, z, △ 10] comprising a supporting substrate position coordinate club [ X, y, z] and strut lever length error △ Io; Z is observations, select 1〇 support rod length of observations, [X1, y1, Z1] is the i-th position of the storage unit coordinates (i over).

[0050] (7)基于构建的滤波估计方程,通过拓展卡尔曼滤波方法对状态量进行估计,估计过程中用到的各个参量的更新过程如式⑷〜(9)所示。 [0050] (7) based on the estimation equation filter constructed to estimate the state quantity by expanding Kalman filter, each of the estimated parameters used in the process as the update process of formula ⑷~ (9) shown in FIG. 其中Rk为杆长测量噪声,Qk为待修正估计直角坐标[x,y,z]和杆长误差Δ Iq的测量噪声。 Wherein the measurement noise Rk is a long lever, Qk estimate Cartesian coordinates [x, y, z] and the lever length measurement noise errors to be corrected Δ Iq. 在微型中央处理器中,通过带入选取的多个位置点直角坐标[0,0,0],[X(2),y(2),z(2)]〜[X(n),y(n),z(n)],进行滤波估算得到杆底直角坐标[x,y,z]以及杆长误差的估计值Δ 1〇。 Micro central processor by selecting a plurality of location points into Cartesian coordinates [0,0,0], [X (2), y (2), z (2)] ~ [X (n), y (n), z (n)], filtering the obtained estimation bottom rod Cartesian coordinates [x, the estimated value y, z] and error Δ 1〇 rod length.

[0051] [0051]

Figure CN105973210BD00073

(4). (4).

Figure CN105973210BD00081

[0057] 不:为tk时刻状态量的一步预测值, [0057] No: tk time step prediction value of the state quantity,

Figure CN105973210BD00082

为tk-时刻状态量的估计值,K为tk时刻的滤波增益矩阵,I为tk时刻均方误差矩阵的一步预测值, Is the estimated value of the state quantity tk- time, K is a filter gain matrix tk time, I is the mean square error at tk step prediction value matrix,

Figure CN105973210BD00083

为tk-dt刻均方误差矩阵的估计值, Tk-dt is the mean square error estimate engraved matrix,

Figure CN105973210BD00084

为tk时刻均方误差矩阵的估计值,Hk为量测方程一阶线性化后的量测矩阵: The estimated value of the mean square error at tk matrix, Hk measurement equation for the first order of the linear measurement matrix:

Figure CN105973210BD00085

为状态量对应的量测方程,上标T表不矩阵的转置,Rk为tk时刻量测噪声,Qk为tk时刻状态噪声阵。 A state quantity corresponding to the measurement equation, the superscript T table is not transposed matrix, Rk is the measurement noise at tk, tk is the time state noise Qk array.

[0058] ⑶将估计得到的杆底直角坐标[x,y,z]和Δ 1〇代入式(10),即可得到测绘仪杆底位置的坐标估计值[A,L,h]。 [0058] ⑶ obtained estimated sole Cartesian coordinates [x, y, z] and Δ 1〇 substituted into the formula (10), to obtain a sole mapper coordinate position estimate [A, L, h].

[0059] [0059]

Figure CN105973210BD00086

(KJ) (KJ)

[0060] [A,L,h]为测绘仪杆底位置的经炜高,A11L1A1分别表示所述存储单元中存储的第一个点的经度、炜度和高度。 [0060] [A, L, h] mapper sole high position by Wei, A11L1A1 represent a longitude of the first point stored in the storage unit, Wei and height.

[0061] 综上所述,本发明设计的一种新型测绘仪杆底位置滤波估计方法,先将测绘仪倾斜画圈旋转,通过记录画圈旋转过程中多个点的位置坐标以及测量的支撑杆杆长,通过拓展卡尔曼滤波算法估计杆底位置坐标,这样可以解决地磁变化和磁场干扰对测绘仪倾斜量修正精度的影响,同时减少了倾斜测量模块中倾角传感器引入的测量误差,提高了测绘仪的倾斜修正精度、使用效率、同时减小了生产成本以及缩小了修正模块的体积和重量。 [0061] In summary, a method for estimating the end position of the filter rod mapper novel design of the present invention, the first mapper inclined rotating circle, circle during rotation by recording a plurality of measuring points and the position coordinates of the support club length, estimated by the Kalman filter algorithm to expand the position coordinates of the sole, which can address the effects of magnetic fields and changes in the geomagnetic mapping tilt amount correction accuracy of the instrument, while reducing the measurement error in the tilt measurement module tilt sensor incorporated, to improve the tilt correction accuracy, the mapper efficiency, while reducing production costs and reducing the volume and weight of the correction module.

[0062] 通过说明和附图,给出了具体实施方式的特定结构的典型实施例,基于本实用新型精神,还可作其他的转换。 [0062] The description and drawings, given the particular structure of the exemplary embodiment of specific embodiments, based on the spirit of the present invention, but also for other transformations. 尽管上述发明提出了现有的较佳实施例,然而,这些内容并不作为局限。 Although the foregoing prior proposed invention, the preferred embodiment, however, the content is not by way of limitation.

[0063] 对于本领域的技术人员而言,阅读上述说明后,各种变化和修正无疑将显而易见。 [0063] For those skilled in the art, upon reading the foregoing description, various changes and modifications will no doubt become apparent. 因此,所附的权利要求书应看作是涵盖本发明的真实意图和范围的全部变化和修正。 Accordingly, the appended claims should be considered all alterations and modifications to cover the true spirit and scope of the present invention. 在权利要求书范围内任何和所有等价的范围与内容,都应认为仍属本发明的意图和范围内。 Within the scope of the appended claims and any and all equivalents ranges content, to be considered within the spirit and scope of the present invention still.

Claims (6)

1. 一种测绘仪杆底位置滤波估计方法,其特征在于,所述方法包括: 将测绘仪的支撑杆的底端安放在待测点; 将所述测绘仪的支撑杆围绕所述待测点倾斜旋转若干圈,记录所述测绘仪旋转过程中多个位置点的位置坐标; 测量所述测绘仪支撑杆长度1〇; 通过拓展卡尔曼滤波算法对所述测绘仪的支撑杆长度和所述测绘仪旋转过程中的多个位置点的位置坐标进行滤波估计,以计算出所述测绘仪的杆底位置坐标。 Bottom position of the filter estimation method for mapping instrument rod, characterized in that, said method comprising: a bottom end of the support bar is placed at the point mapper tested; the support bars around the mapper test a plurality of position coordinate points inclined rotating ring, the mapper recording a plurality of positions during rotation point; measuring the length of the support bar 1〇 mapper; Kalman filter by expanding the length of the support bar and the mapper filtering the estimated positions of said plurality of positional coordinates of points mapper during rotation, to calculate the position coordinates of the sole of the mapper.
2. 根据权利要求1所述的方法,其特征在于,所述方法包括: 所述测绘仪的支撑杆围绕所述支撑杆底端以8字型或圆形方式倾斜旋转。 2. The method according to claim 1, characterized in that, said method comprising: a mapper shaped support bar 8 to rotate about the inclined circular or bottom end of the support bar.
3. 根据权利要求1所述的方法,其特征在于,所述方法还包括: 将所述测绘仪的支撑杆倾斜旋转过程中的采集的位置坐标存储至所述测绘仪的存储单元中; 输入所述测绘仪的支撑杆杆长,并于所述测绘仪的微型处理器中通过拓展卡尔曼滤波算法对所述测绘仪的支撑杆长度和存储在所述存储单元中的位置坐标进行滤波估计。 3. The method according to claim 1, wherein said method further comprises: the inclined position of the support bars mapper coordinate storing acquired during rotation to the storage unit in the mapper; input the mapper support club length, and in the micro-processor mapper filtered estimate of position coordinates of the support rod length mapper and stored in the storage unit by expanding Kalman filter .
4. 根据权利要求3所述的方法,其特征在于,所述方法包括: 通过拓展卡尔曼滤波估计算法对所述测绘仪的支撑杆杆底位置坐标及支撑杆的杆长误差A 1〇进行估计计算,根据拓展卡尔曼状态方程Xk = FX1^1和量测方程 4. The method according to claim 3, characterized in that, said method comprising: A lever length error 1〇 the club mapper support strut coordinates and the bottom position by expanding Kalman filter estimation algorithm estimation calculation, according to the state equation of the Kalman expand Xk = FX1 ^ 1 and the measurement equation
Figure CN105973210BC00021
计算得出; 其中F为单位矩阵,Xk-^tk-i时刻的状态量X,Xk为tk时刻的状态量,状态量X=[x,y,z, A 1〇],包含支撑杆杆底位置坐标[x,y,z]及支撑杆的杆长误差Λ Io;Z为观测量,选取支撑杆长度Io为观测量,[X1,y1,Z1]为所述存储单元中的第i个点的位置坐标。 Calculated; wherein F is the unit matrix, the state quantity X Xk- ^ tk-i is the time, at tk Xk is the state quantity, the state quantity X = [x, y, z, A 1〇], comprising a support club bottom position coordinate [x, y, z] and strut lever length error Λ Io; Z is observations, Io is the length of the support bar select observations, [X1, y1, Z1] is the i-th storage unit position coordinates of the points.
5. 根据权利要求4所述的方法,其特征在于,所述方法还包括: 按照 The method according to claim 4, characterized in that the method further comprises: in accordance with
Figure CN105973210BC00022
Figure CN105973210BC00023
五个迭代更新方程,通过拓展卡尔曼滤波方法估计状态量; 其中, Five iterative update equation, by expanding the amount of estimated state Kalman filter; wherein,
Figure CN105973210BC00024
为tk时刻状态量的一步预测值, Tk state for the amount of time step prediction value,
Figure CN105973210BC00025
为tk-dt刻状态量的估计值,K为tk时刻的滤波增益矩阵,为tk时刻均方误差矩阵的一步预测值, Tk-dt is the estimated value of the state quantity engraved, K is a filter gain matrix at tk, tk is the time step prediction value of the mean square error matrix,
Figure CN105973210BC00026
为以-:时刻均方误差矩阵的估 Is to: - time mean square error estimation matrix
Figure CN105973210BC00027
计值, Terms,
Figure CN105973210BC00028
为tk时刻均方误差矩阵的估计值,Hk为量测方程一阶线性化后的量测矩阵, Tk is the time value of the mean square error estimation matrix, Hk measurement equation for the first order of the linear measurement matrix,
Figure CN105973210BC00029
为状态量 The state quantity
Figure CN105973210BC000210
_对应的量测方程,上标T表不矩阵的转置,Rk为tk时刻量测噪声,Qk为tk时刻状态噪声阵。 _ Corresponding measurement equation, the superscript T table is not transposed matrix, Rk is the measurement noise at tk, tk is the time state noise Qk array.
6. 根据权利要求5所述的方法,其特征在于,所述方法还包括: 将估计得到的杆底直角坐标[X,y,z]和杆长误差A 1〇代入 6. The method according to claim 5, characterized in that, said method further comprising: sole Cartesian coordinates [X, y, z] and the estimated error stem length A 1〇 substituting
Figure CN105973210BC000211
式中,即可得到测绘仪杆底位置的经炜高估计值[A,L,h]; 其中,r为地球半径,A11IAh1分别表示所述存储单元中存储的第一个点的经度、炜度和高度。 In the formula, to obtain a sole mapper high position estimate by Wei [A, L, h]; where, r is the radius of the earth, A11IAh1 represent a longitude of the first point stored in the storage unit, Wei and height.
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