CN114001726B - Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field - Google Patents
Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field Download PDFInfo
- Publication number
- CN114001726B CN114001726B CN202111238451.5A CN202111238451A CN114001726B CN 114001726 B CN114001726 B CN 114001726B CN 202111238451 A CN202111238451 A CN 202111238451A CN 114001726 B CN114001726 B CN 114001726B
- Authority
- CN
- China
- Prior art keywords
- temperature
- drift
- fiber
- optic gyroscope
- multivariate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C19/00—Gyroscopes; Turn-sensitive devices using vibrating masses; Turn-sensitive devices without moving masses; Measuring angular rate using gyroscopic effects
- G01C19/58—Turn-sensitive devices without moving masses
- G01C19/64—Gyrometers using the Sagnac effect, i.e. rotation-induced shifts between counter-rotating electromagnetic beams
- G01C19/72—Gyrometers using the Sagnac effect, i.e. rotation-induced shifts between counter-rotating electromagnetic beams with counter-rotating light beams in a passive ring, e.g. fibre laser gyrometers
- G01C19/721—Details
Abstract
The invention provides a fiber-optic gyroscope temperature drift compensation device and method based on a multi-element temperature field. The temperature drift compensation device of the fiber-optic gyroscope comprises: the thermal imager is used for analyzing the actual distribution of the temperature field of the fiber-optic gyroscope; a temperature sensor for measuring the temperature of the fiber optic ring or housing; the multi-channel AD temperature acquisition board converts the analog signals into digital signals and packages and outputs the digital signals; and the compensation computer is used for drift decomposition and multivariate temperature information calculation, and training, predicting and compensating the temperature drift model. The temperature drift compensation method of the fiber-optic gyroscope comprises the following steps: determining the number and the attachment positions of the temperature sensors according to the distribution of the temperature fields; acquiring gyro drift, and extracting temperature drift by using Variational Modal Decomposition (VMD); calculating multivariate temperature information comprising temperature of the measuring points, temperature change rate of the measuring points and temperature gradient among the measuring points; and training a fiber-optic gyroscope temperature drift model based on the multivariate temperature information and the SVM/SVR, predicting and outputting in a compensation mode.
Description
Technical Field
The invention belongs to the field of fiber optic gyroscopes, relates to a signal acquisition and digital processing method, and particularly relates to a fiber optic gyroscope temperature drift compensation device and method based on a multi-element temperature field.
Background
The fiber optic gyroscope is a fiber optic ring type inertial sensor based on the Sagnac effect, has the characteristics of low cost, high reliability, wide dynamic range, large development space and the like, and is widely applied to the fields of tactical weapons, aircrafts, ships, consumer markets and the like. However, since the fiber-optic gyroscope often works in a severe environment, the fiber-optic ring is susceptible to environmental temperature to generate non-reciprocal errors, which brings gyroscope drift strongly related to temperature.
The existing fiber optic gyroscope temperature drift and compensation methods comprise least two-way fitting (LSF), a plurality of neural network modeling and support vector machine/support vector regression (SVM/SVR) modeling, but the methods have certain defects. The LSF model is simple and easy to realize in engineering, but the nonlinear regression capability is weak; the neural network modeling nonlinear approximation capability is strong, but the environment adaptability is poor, and an overfitting phenomenon can occur; the SVM/SVR has strong nonlinear approximation, can overcome the phenomenon of over-fitting, has better generalization capability, and is easily influenced by non-temperature noise in sample data. With the continuous improvement of the precision of the fiber-optic gyroscope, in order to ensure the environmental adaptability, the temperature drift modeling and compensation become problems which need to be solved urgently.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a fiber-optic gyroscope temperature drift compensation device and method based on a multi-element temperature field, and the device and method can be used for solving the requirement of high-precision fiber-optic gyroscope on environmental adaptability.
According to a first aspect of the invention, a fiber-optic gyroscope temperature drift compensation device based on a multivariate temperature field comprises a thermal imager, a temperature sensor and a temperature sensor, wherein the thermal imager is used for detecting and analyzing the actual distribution of the temperature field of the fiber-optic gyroscope in a variable-temperature environment; a temperature sensor for measuring a temperature change at the attachment point; the multi-channel AD temperature acquisition board converts the analog signals of the temperature of the measured point into digital signals and packs and sends the data to the compensation computer; and the compensation computer is used for training a temperature drift model based on the multivariate temperature field and the SVM/SVR, predicting the temperature drift of the gyroscope in the actual work of the gyroscope and obtaining compensated gyroscope output.
Specifically, the number and attachment positions of the sensors are determined according to the actual distribution of the temperature field by the temperature sensors; the analog temperature sensor has the advantages of small volume, high reliability, high precision, large measuring range, easy installation, no influence on the structural performance of the fiber optic gyroscope and the like.
Specifically, the compensation computer is further configured to measure an original output of the fiber optic gyroscope; and separating non-temperature noise by using Variation Mode Decomposition (VMD), and judging data correlation by using sample entropy to obtain the temperature drift of the fiber-optic gyroscope.
Specifically, the compensation computer is used for calculating the temperature change rate at the measuring points and the temperature gradient between the measuring points after acquiring the multi-channel temperature data sent by the multi-channel AD temperature acquisition board; and the compensation computer respectively takes the temperature drift and the multivariate temperature information of the fiber-optic gyroscope as the sample output and the sample input of the SVM/SVR and is used for training a fiber-optic gyroscope temperature drift model.
According to a second aspect of the invention, a method for compensating temperature drift of a fiber-optic gyroscope based on a multivariate temperature field comprises the following steps:
step 41, removing the non-temperature noise IMF component of the fiber-optic gyroscope by adopting Variational Modal Decomposition (VMD) and sample entropy according to the gyro drift obtained in the step 3, and extracting the gyro temperature drift;
step 42, calculating the temperature change rate of the measuring points and the temperature gradient among the measuring points according to the temperature data of each measuring point obtained in the step 3;
and 6, calculating the multivariate temperature information of the gyroscope during actual working, predicting through the training model in the step 5, and compensating the temperature drift.
Further, in the step 1, a thermal imager is used for respectively shooting the distribution of the temperature field of the circular section of the gyroscope and the axial temperature field of the sensitive shaft, and a steady-state temperature field is assumed to appear after the optical fiber gyroscope works stably; and the actual distribution of the temperature field also determines the number and the attachment positions of the multi-channel analog temperature sensors in the step 2.
Further, in the step 3, in order to adapt to various temperature working conditions, a multi-section temperature changing rate is adopted in the temperature changing scheme: +/-0.5 ℃/min, +/-1 ℃/min, +/-2 ℃/min and +/-3 ℃/min, and the temperature range is-40 ℃ to 60 ℃; and step 3, a multi-channel AD temperature acquisition board is independently designed by integrating a plurality of AD chips and a master control MCU chip, and multi-channel temperature analog signals are converted into digital signals and are packaged and sent to a compensation computer.
Further, the step 41 specifically includes:
(1) original output signal omega of optical fiber gyroscope m Minus the component omega of the direction of rotation of the earth ie cos L, to obtain the fiber-optic gyroscope drift, where ω ie Representing the rotational angular velocity of the earth, and L representing the latitude of the location of the testing environment;
(2) setting a VMD parameter;
(3) estimating center frequency ω of decomposed components k And reconstructing the corresponding signal component u k K represents the kth IMF component;
(4) setting a sample entropy parameter, and calculating the sample entropy of each component according to the following formula:
in the formula, m represents an embedding dimension, r represents fault tolerance, and B is an intermediate variable; and separating the temperature drift component and the non-temperature noise according to the sample entropy.
Further, the temperature change rate in step 42 is obtained according to the following formula:
in the formula, n is the number of the temperature sensors,
and
indicates that the ith temperature sensor is respectively at t k And t k-1 Measured temperature data of a time instant; the temperature gradient is estimated as follows:
in the formula (I), the compound is shown in the specification,
and
respectively indicates that the (i + 1) th temperature sensor and the ith temperature sensor are at t k The measured temperature data of the time of day,
is the distance between the (i + 1) th temperature sensor and the position where the (i) th temperature sensor is attached.
Further, the step 6 specifically includes:
(1) setting SVM/SVR parameters and kernel function parameters thereof;
(2) respectively taking gyro temperature drift and multivariate temperature information (measuring point temperature, measuring point temperature change rate and temperature gradient between measuring points) as sample output and input, and training a fiber optic gyro temperature drift model;
(3) and predicting the temperature drift through the training model in different temperature changing working condition environments to obtain the compensated output of the fiber-optic gyroscope.
The invention has the following positive effects:
compared with the prior art, the method has the remarkable advantages of more accurate model, high compensation precision, simple structure, suitability for complex working conditions and the like, and is particularly shown in the following steps: the construction of the multi-element temperature field, namely determining the number and the attachment positions of the temperature sensors according to the actual temperature field, and acquiring and calculating multi-element temperature information; the gyro temperature drift is judged and extracted through VMD decomposition and sample entropy, and the defects that the EMD and the derivation method have strict requirements on sample data and the like are overcome; the SVM/SVR modeling based on the multivariate temperature information is closer to a fiber-optic gyroscope temperature drift theoretical model, and replaces single sample input in the prior art.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the principles of the invention.
Fig. 1 is a schematic diagram of an architecture of a fiber-optic gyroscope temperature drift compensation device based on a multivariate temperature field according to at least one embodiment of the invention.
Fig. 2 is a flowchart of a method for compensating temperature drift of a fiber-optic gyroscope based on a multivariate temperature field according to at least one embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant disclosure and are not to be considered as limiting. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments of the present invention may be combined with each other without conflict. The present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In at least one embodiment of the invention, the invention provides a fiber-optic gyroscope temperature drift compensation device and method based on a multivariate temperature field.
As shown in fig. 1, the fiber-optic gyroscope temperature drift compensation device based on the multivariate temperature field provided by the invention comprises a thermal imager 1, a fiber-optic gyroscope 2, a temperature sensor 3, a multi-channel AD temperature acquisition board 4 and a compensation computer 5. The thermal imager 1 is used for detecting and analyzing the actual distribution of the temperature field of the fiber-optic gyroscope 2; the temperature sensor 3 is used for measuring the temperature of the optical fiber ring or the shell; the multi-channel AD temperature acquisition board 4 converts the temperature analog signal into a digital signal; and the compensation computer 5 is used for measuring the original output of the gyroscope, calculating multivariate temperature information according to the temperature data of each measured point, establishing a temperature drift model and performing gyroscope compensation.
Determining the number and the attachment positions of the temperature sensors 3 according to the temperature field analyzed by the thermal imager 1; a plurality of AD chips and MCU main control chips are integrated on the multichannel AD temperature acquisition board 4, the number of AD channels can be set according to the number of the temperature sensors 3, and data are packaged and sent to the compensation computer 5; the compensation computer 5 is used for measuring drift original data of the fiber-optic gyroscope 2, and extracting temperature drift of the gyroscope by using VMD decomposition and sample entropy judgment; on the other hand, multi-element temperature information is calculated according to the temperature data, wherein the multi-element temperature information comprises measuring point temperature, measuring point temperature change rate and temperature gradient among measuring points; and for temperature drift model training, prediction and compensation.
The temperature drift compensation device of the fiber-optic gyroscope provided by the invention can compensate and output the temperature drift of the gyroscope, and as shown in figure 2, the temperature drift compensation device of the fiber-optic gyroscope comprises the following steps:
s1: the temperature field was analyzed.
S2: the number of temperature sensors and attachment positions are determined.
Specifically, the thermal imager 1 is used for analyzing the actual distribution of the temperature field of the fiber-optic gyroscope 2, and a temperature sensor is attached to a position with a relatively obvious isotherm/surface area; the analog temperature sensor has the advantages of small size, high precision, large measuring range, high reliability, easy installation and the like.
S3: and determining a temperature change scheme, and performing a gyro temperature change test.
S31: measuring the output of the gyroscope;
s32: measuring the temperature of the gyroscope;
specifically, the temperature range in the temperature variation scheme can be set to, but is not limited to, -40 ℃ to 60 ℃; the multi-stage temperature change rate can be set to be but is not limited to +/-0.5 ℃/min, +/-1 ℃/min, +/-2 ℃/min and +/-3 ℃/min; the temperature change test can be carried out in a rotary table incubator, and the sensitive axis of the fiber-optic gyroscope 2 is installed in a pointing manner.
Further, the analog signals are converted into digital signals by using a multi-channel AD temperature acquisition board 4, and the digital signals are packaged and sent to a compensation computer 5; DSP or FPGA can be selected as the main control chip of the acquisition board, and the number of AD channels can be freely configured according to the number of the temperature sensors.
S41: VMD decomposition and sample entropy analysis;
specifically, after the compensation computer 5 measures the gyro output signal, the method further includes:
(1) calculating the fiber optic gyroscope drift according to the following formula:
ε＝ω m -ω ie cos L
wherein, ω is m Representing the gyro output signal, ω ie cos L represents the Earth's own natural direction component, ω ie Representing the rotational angular velocity of the earth, and L representing the latitude of the testing environment;
(2) setting a VMD parameter;
(3) estimating center frequency ω of decomposed components k And reconstructing the corresponding signal component u k K represents the kth IMF component;
(4) setting a sample entropy parameter, and calculating the sample entropy of each component according to the following formula:
in the formula, m represents an embedding dimension, r represents fault tolerance, and B is an intermediate variable; and separating the temperature drift component and the non-temperature noise according to the sample entropy.
S42: calculating multivariate temperature information;
specifically, the multivariate temperature information comprises measuring point temperatures, measuring point temperature change rates and temperature gradients among measuring points, wherein the temperature change rates and the temperature gradients are calculated by the measuring point temperatures obtained by the compensation computer 5.
Further, the temperature change rate is obtained according to the following formula:
wherein n is the number of the temperature sensors,
and
indicating the ith temperature transmissionThe sensors are respectively at t k And t k-1 Measured temperature data of a time instant;
further, the temperature gradient is estimated as follows:
in the formula (I), the compound is shown in the specification,
and
respectively indicates that the (i + 1) th temperature sensor and the ith temperature sensor are at t k The measured temperature data of the time of day,
is the distance between the (i + 1) th temperature sensor and the position where the (i) th temperature sensor is attached.
S5: training an SVM/SVR temperature drift model;
s6: and (5) predicting and compensating output.
Specifically, the training, prediction and compensation of the temperature drift model comprises the following steps:
(1) taking the temperature drift of the gyroscope as the output of model training, and taking multivariate temperature information (temperature of measuring points, temperature change rate of the measuring points and temperature gradient between the measuring points) as the sample input of the model training;
(2) setting SVM/SVR parameters, and training a temperature drift model:
where x is the sample input, x k To support the vector, a i And
is a Lagrange multiplier, C is a penalty factor, g is a kernel function parameter, and b is a hyperplane intercept constant.
(3) And (4) performing experiments under various variable temperature working conditions, and predicting temperature drift through a training model to obtain compensated output of the fiber optic gyroscope.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of description and are not intended to limit the scope of the invention. It will be apparent to those skilled in the art that other variations or modifications may be made on the above invention and still be within the scope of the invention.
Claims (8)
1. A fiber-optic gyroscope temperature drift compensation device based on a multivariate temperature field, which is characterized by comprising:
the thermal imager is used for detecting and analyzing the actual distribution of the temperature field of the fiber-optic gyroscope in the variable temperature environment;
the temperature sensor is used for measuring the temperature of the optical fiber ring or the shell at the attaching point;
the multi-channel AD temperature acquisition board converts the analog signals into digital signals, packs the data and sends the data to the compensation computer;
and the compensation computer is used for drift decomposition, multivariate temperature information calculation, temperature drift model training, prediction and compensation.
2. The device for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as claimed in claim 1, wherein: the temperature sensor is an analog temperature sensor and is attached to a position which is obviously distinguished on an isotherm/isotherm surface according to the actual distribution of a temperature field.
3. The device for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as claimed in claim 1, wherein: the compensation computer is used for measuring drift original data of the fiber-optic gyroscope and judging and extracting temperature drift of the gyroscope by using VMD decomposition and sample entropy; on the other hand, multi-element temperature information is calculated according to the temperature data, wherein the multi-element temperature information comprises measuring point temperature, measuring point temperature change rate and temperature gradient among measuring points; and for temperature drift model training, prediction and compensation.
4. A fiber-optic gyroscope temperature drift compensation method based on a multivariate temperature field is characterized by comprising the following steps:
step 1, detecting and analyzing the actual distribution of the temperature field of the measured fiber-optic gyroscope by using a thermal imager or other temperature imaging devices;
step 2, attaching a plurality of analog temperature sensors to the surface of the optical fiber ring or the shell of the fiber-optic gyroscope according to the temperature field distribution;
step 3, determining a temperature change scheme, and performing a temperature change test on the fiber optic gyroscope to obtain the drift of the gyroscope and the temperature of each measuring point;
step 41, removing non-temperature noise IMF components by adopting Variational Modal Decomposition (VMD) and sample entropy according to the variable temperature test gyro drift output, and extracting gyro temperature drift;
step 42, calculating multivariate temperature information according to the temperature of each measuring point measured by the temperature change test;
step 5, training a fiber optic gyroscope temperature drift model by using a support vector machine/support vector regression (SVM/SVR) according to the obtained temperature drift and the multivariate temperature information;
and 6, calculating the multivariate temperature information of the gyroscope during actual working, predicting through the model trained in the step 5, and compensating the temperature drift.
5. The method for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as claimed in claim 4, wherein the method comprises the following steps: and 3, when multi-point temperature acquisition is carried out, analog-to-digital conversion is carried out by using the multi-channel AD temperature acquisition board, and the number of the measurement channels of the AD temperature acquisition board can be freely configured according to the number of the temperature sensors.
6. The method for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as set forth in claim 4, wherein the method comprises the following steps: the step 41 specifically includes: (1) collecting the original output of a gyroscope; (2) calculating the gyro drift; (3) setting VMD parameterCounting; (4) estimating a center frequency ω of a kth IMF component k And reconstructing the corresponding signal component u k (ii) a (5) And selecting according to the sample entropy.
7. The method for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as claimed in claim 4, wherein the method comprises the following steps: the multivariate temperature information in step 42 comprises: measuring point temperature, temperature change rate at the measuring point and temperature gradient between the measuring points.
8. The method for compensating the temperature drift of the fiber-optic gyroscope based on the multivariate temperature field as claimed in claim 4, wherein the method comprises the following steps: the step 5 specifically includes: (1) the gyro temperature drift is used as the output of model training, the multivariate temperature information is used as the sample input of the model training, and the sample input dimension is determined by the multivariate temperature information dimension; (2) SVM/SVR parameters are set, and a temperature drift model is trained.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111238451.5A CN114001726B (en) | 2021-10-25 | 2021-10-25 | Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111238451.5A CN114001726B (en) | 2021-10-25 | 2021-10-25 | Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114001726A CN114001726A (en) | 2022-02-01 |
| CN114001726B true CN114001726B (en) | 2022-08-30 |
Family
ID=79923675
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111238451.5A Active CN114001726B (en) | 2021-10-25 | 2021-10-25 | Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114001726B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11808780B1 (en) * | 2022-05-20 | 2023-11-07 | Honeywell International Inc. | Inertial sensor error modeling and compensation, and system for lifetime inertial sensor calibration and navigation enhancement |
| CN117517565B (en) * | 2023-11-27 | 2024-04-19 | 广州市建筑材料工业研究所有限公司 | Method for calculating temperature drift in furnace in building material incombustibility test in real time |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013035A (en) * | 2007-02-08 | 2007-08-08 | 北京航空航天大学 | Neural net based temperature compensating optical fibre gyroscope |
| CN106022212A (en) * | 2016-05-04 | 2016-10-12 | 东南大学 | Gyroscope temperature drift modeling method |
| CN107621269A (en) * | 2016-07-15 | 2018-01-23 | 北京计算机技术及应用研究所 | Fiber Optic Gyroscope Temperature Drift error compensating method |
| CN109099937A (en) * | 2018-10-10 | 2018-12-28 | 湖南航天机电设备与特种材料研究所 | A kind of optical fibre gyro zero bias temperature error compensating method |
| CN110595508A (en) * | 2019-09-26 | 2019-12-20 | 湖南航天机电设备与特种材料研究所 | Optical fiber gyroscope scale factor error compensation method |
| CN111854799A (en) * | 2020-07-13 | 2020-10-30 | 北京思卓博瑞科技有限公司 | Temperature compensation method and device of optical fiber gyroscope and optical fiber gyroscope |
-
2021
- 2021-10-25 CN CN202111238451.5A patent/CN114001726B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013035A (en) * | 2007-02-08 | 2007-08-08 | 北京航空航天大学 | Neural net based temperature compensating optical fibre gyroscope |
| CN106022212A (en) * | 2016-05-04 | 2016-10-12 | 东南大学 | Gyroscope temperature drift modeling method |
| CN107621269A (en) * | 2016-07-15 | 2018-01-23 | 北京计算机技术及应用研究所 | Fiber Optic Gyroscope Temperature Drift error compensating method |
| CN109099937A (en) * | 2018-10-10 | 2018-12-28 | 湖南航天机电设备与特种材料研究所 | A kind of optical fibre gyro zero bias temperature error compensating method |
| CN110595508A (en) * | 2019-09-26 | 2019-12-20 | 湖南航天机电设备与特种材料研究所 | Optical fiber gyroscope scale factor error compensation method |
| CN111854799A (en) * | 2020-07-13 | 2020-10-30 | 北京思卓博瑞科技有限公司 | Temperature compensation method and device of optical fiber gyroscope and optical fiber gyroscope |
Non-Patent Citations (5)
| Title |
|---|
| 一种基于变分模态分解和样本熵的MEMS陀螺去噪方法;刘洋等;《仪表技术与传感器》;20210615(第6期);第90-94页 * |
| 光纤陀螺温度特性与补偿方法研究;刘世昌;《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》;20180315(第03期);全文 * |
| 光纤陀螺闭环控制与温度补偿技术研究;李锷;《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》;20100515(第05期);全文 * |
| 光纤陀螺零偏漂移的温度特性与补偿;侯宏录等;《自动化仪表》;20190320;第40卷(第3期);第59-68页 * |
| 基于PSO-SVR的光纤陀螺温度误差建模与实时补偿;黄春福等;《光子学报》;20200102;第48卷(第12期);第1206002-1至1206002-8页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114001726A (en) | 2022-02-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114001726B (en) | Fiber-optic gyroscope temperature drift compensation device and method based on multi-element temperature field | |
| Poddar et al. | A comprehensive overview of inertial sensor calibration techniques | |
| CN110325833B (en) | System for accurately measuring structure and method thereof | |
| CN109001787A (en) | A kind of method and its merge sensor of solving of attitude and positioning | |
| EP1552246A2 (en) | Method and system for processing pulse signals within an inertial navigation system | |
| CN103256929A (en) | Estimation of conventional inertial sensor errors with atomic inertial sensor | |
| EP3542131A1 (en) | Self-calibrating inertial measurement system and method | |
| CN105737793B (en) | Rolling angle measurement unit and measuring method | |
| CN108225374A (en) | A kind of Allan methods of analysis of variance of blending inheritance algorithm | |
| US9594169B2 (en) | Altitude detecting unit, loading/driving apparatus, and altitude detecting method | |
| Geist et al. | Gravity-based characterization of three-axis accelerometers in terms of intrinsic accelerometer parameters | |
| CN107270902B (en) | MEMS inertial measurement unit with cross-axis coupling error compensation | |
| CN114370930A (en) | Method for measuring satellite structure micro-angle vibration by using MHD micro-angle vibration sensor | |
| CN103954351A (en) | Measuring method of micro angle vibration of spacecraft | |
| Zhong et al. | A new drone accelerometer calibration method | |
| US6493651B2 (en) | Method and system for determining magnetic attitude | |
| Choi et al. | Calibration of inertial measurement units using pendulum motion | |
| Wang et al. | Temperature compensation for gyroscope free micro inertial measurement unit | |
| Ruizenaar et al. | Gyro bias estimation using a dual instrument configuration | |
| Li et al. | Error modeling, calibration, and nonlinear interpolation compensation method of ring laser gyroscope inertial navigation system | |
| Zhao et al. | Evaluation on the fiber optic gyroscope dynamic angle measurement performance using a rotary table angle encoder | |
| CN112902954A (en) | Tower frame shaking sensor and tower frame shaking angle measuring method | |
| CN116147666B (en) | Method for testing long-range performance of high-precision optical gyroscope based on angular position | |
| DONG et al. | A System-level Calibration Method for Laser Gyro SINS | |
| CN108489459B (en) | Attitude sensing system and inclination angle measuring method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |