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CN-122015915-A - Automatic calibration method and system of inertial measurement unit and electronic equipment

CN122015915ACN 122015915 ACN122015915 ACN 122015915ACN-122015915-A

Abstract

The application provides an automatic calibration method and system of an inertial measurement unit and electronic equipment, and relates to the technical field of sensors, wherein the method comprises the steps of constructing an IMU multi-mode calibration environment and deploying a plurality of groups of reference sensors; designing a working environment test parameter table, performing simulation test on the IMU to be calibrated, synchronously recording multi-mode test data and multi-mode reference data of the IMU, establishing an error parameter model, constructing a calibration multi-objective function, performing minimum solution on the error parameter model, and performing closed-loop optimization correction on the IMU to be calibrated. According to the application, the technical problems that in the prior art, because IMU error calibration is usually carried out under an ideal environment state, complex coupling errors caused by multi-factor coupling effects are ignored, the compensation accuracy of calibration parameters under complex actual working conditions is seriously reduced, the IMU output drift is remarkably increased, and the output accuracy of the IMU under a full working condition environment and the robustness of the calibration parameters are improved are solved.

Inventors

  • YU YINGYING

Assignees

  • 深圳市瑞芬科技有限公司

Dates

Publication Date
20260512
Application Date
20260411

Claims (10)

  1. 1. An automated calibration method for an inertial measurement unit, comprising: Setting up an IMU multi-mode calibration environment, integrating a high-precision temperature and humidity control module, a vibration simulation device, an electromagnetic interference device and an air pressure control module by the IMU multi-mode calibration environment, and deploying a plurality of groups of reference sensors in the IMU multi-mode calibration environment; Designing an IMU working environment test parameter table, driving the IMU multi-mode calibration environment to perform simulation test on the IMU to be calibrated according to the IMU working environment test parameter table, and synchronously recording IMU multi-mode test data and multi-mode reference data of the plurality of groups of reference sensors; performing error source decomposition and quantization on the IMU multi-mode test data by combining the multi-mode reference data, and establishing an IMU error parameter model; and constructing a calibration multi-objective function, carrying out minimized solution on the IMU error parameter model based on the calibration multi-objective function, determining a target IMU calibration parameter, and carrying out closed-loop optimization correction on the IMU to be calibrated through the target IMU calibration parameter.
  2. 2. An automated calibration method for an inertial measurement unit according to claim 1, wherein designing the IMU operating environment test parameter table comprises: Defining IMU working environment factor information, wherein the IMU working environment factor information comprises temperature and humidity, vibration, electromagnetic interference and air pressure; Analyzing a test boundary of the working application scene of the IMU to be calibrated according to the IMU working environment factor information to obtain an IMU working environment factor boundary; constructing a multi-modal parameter combination strategy, wherein the multi-modal parameter combination strategy comprises a working scene coverage and a test parameter gradient; and designing test parameters for the boundary of the IMU working environment factors based on the multi-mode parameter combination strategy, and generating an IMU working environment test parameter table.
  3. 3. The automated calibration method of an inertial measurement unit of claim 2, wherein performing test parameter design on the IMU operating environment factor boundary based on the multi-modal parameter combination strategy, generating an IMU operating environment test parameter table, comprises: carrying out single-mode and multi-mode scene coverage analysis on the boundary of the IMU working environment factors based on the multi-mode parameter combination strategy to obtain environment factor scene coverage parameter combination; Determining the environment test parameter selection density according to the IMU calibration precision requirement; Selecting density according to the environment test parameters, and respectively carrying out test gradient division on the environment factor scene coverage parameter combination to obtain an environment factor scene parameter step set; And designing the test parameters of the environmental factor scene coverage parameter combination based on the environmental factor scene parameter step length set, and generating an IMU working environment test parameter table.
  4. 4. The automated calibration method of an inertial measurement unit of claim 1, wherein performing error source decomposition and quantization on the IMU multi-modal test data in combination with the multi-modal reference data, and establishing an IMU error parameter model, comprises: performing association matching on the multi-mode reference data and the IMU multi-mode test data according to a time stamp to obtain multi-mode reference sequence data and IMU multi-mode test sequence data; Defining an IMU error type, wherein the IMU error type comprises deterministic errors, random errors and environment coupling errors; performing error source decomposition on the IMU multi-mode test sequence data according to the IMU error type to obtain an IMU test error source signal; And carrying out quantitative modeling on the IMU test error source signal by combining the multi-mode reference sequence data, and establishing an IMU error parameter model.
  5. 5. The automated calibration method of an inertial measurement unit of claim 4, wherein performing error source decomposition on the IMU multi-modal test sequence data according to the IMU error type to obtain an IMU test error source signal, comprising: selecting a signal wavelet basis function according to the characteristic information of the IMU error type; Performing multi-scale decomposition on the IMU multi-mode test sequence data by adopting the signal wavelet basis function to obtain an IMU signal approximation coefficient and an IMU signal detail coefficient; Performing error source correlation extraction on the IMU signal approximation coefficients and IMU signal detail coefficients to obtain IMU error source correlation signal coefficients; And sequentially carrying out error signal reconstruction based on the IMU error source correlation signal coefficients to obtain an IMU test error source signal.
  6. 6. An automated calibration method for an inertial measurement unit according to claim 4, wherein quantitatively modeling the IMU test error source signal in combination with the multi-modal reference sequence data to create an IMU error parameter model comprises: obtaining a deterministic error signal, a random error signal and an environment coupling error signal according to the IMU test error source signal; Respectively carrying out error fitting on the deterministic error signal, the random error signal and the environment coupling error signal by combining the multi-mode reference sequence data to generate a deterministic error parameter model, a random error parameter model and an environment coupling error parameter model; and carrying out fusion optimization on the deterministic error parameter model, the random error parameter model and the environment coupling error parameter model, and establishing an IMU error parameter model.
  7. 7. An automated calibration method for an inertial measurement unit according to claim 1, wherein performing a minimization solution to the IMU error parameter model based on the calibration multi-objective function, determining target IMU calibration parameters, comprises: performing calibration analysis on the IMU error parameter model, and initializing a calibration parameter particle space; performing fitness calculation on the calibration parameter particle space based on the calibration multi-objective function to obtain an IMU parameter particle fitness set; And introducing a neighborhood topology updating mechanism, carrying out iterative updating evaluation and minimized solving in the calibration parameter particle space based on the IMU parameter particle fitness set until a convergence condition is preset, and determining a target IMU calibration parameter.
  8. 8. An automated calibration method for an inertial measurement unit according to claim 1, wherein performing closed-loop optimization correction on the IMU to be calibrated by the target IMU calibration parameters comprises: Performing test verification comparison on the IMU to be calibrated through the target IMU calibration parameters to obtain IMU error distribution parameters; And performing closed-loop optimization correction on the target IMU calibration parameters based on the IMU error distribution parameters by adopting a PID controller.
  9. 9. An automated calibration system for an inertial measurement unit, characterized by the steps for implementing an automated calibration method for an inertial measurement unit according to any one of claims 1 to 8, the automated calibration system comprising: The system comprises a calibration environment building module, a calibration environment monitoring module and a calibration environment monitoring module, wherein the calibration environment building module is used for building an IMU multi-mode calibration environment, the IMU multi-mode calibration environment is integrated with a high-precision temperature and humidity control module, a vibration simulation device, an electromagnetic interference device and an air pressure control module, and a plurality of groups of reference sensors are deployed in the IMU multi-mode calibration environment; The simulation test module is used for designing an IMU working environment test parameter table, driving the IMU multi-mode calibration environment to perform simulation test on the IMU to be calibrated according to the IMU working environment test parameter table, and synchronously recording IMU multi-mode test data and multi-mode reference data of the plurality of groups of reference sensors; the error decomposition module is used for carrying out error source decomposition and quantization on the IMU multi-mode test data by combining the multi-mode reference data, and establishing an IMU error parameter model; And the closed loop correction module is used for constructing a calibration multi-objective function, carrying out minimized solution on the IMU error parameter model based on the calibration multi-objective function, determining a target IMU calibration parameter, and carrying out closed loop optimization correction on the IMU to be calibrated through the target IMU calibration parameter.
  10. 10. An electronic device, comprising: At least one processor; a memory communicatively coupled to the at least one processor; Wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of an automated calibration method of an inertial measurement unit according to any one of claims 1 to 8.

Description

Automatic calibration method and system of inertial measurement unit and electronic equipment Technical Field The application relates to the technical field of sensors, in particular to an automatic calibration method and system of an inertial measurement unit and electronic equipment. Background The inertial measurement unit is used as a core sensor for measuring the acceleration and the angular velocity of an object, and the accuracy of the inertial measurement unit directly determines the reliability of system gesture sensing and navigation positioning, so that the inertial measurement unit is widely applied to core stable control, motion gesture measurement and control and dynamic balance adjustment of a humanoid robot, autonomous navigation positioning of an AGV/AMR, low-speed unmanned logistics vehicles and unmanned system high-accuracy measurement and control under various complex environments. To ensure accuracy, the IMU must be calibrated before it can be put into service to determine and compensate for its inherent sensor errors. However, the existing calibration method is mostly carried out under ideal environmental conditions of a laboratory, and the comprehensive influence of multi-factor coupling effects such as temperature and humidity change, random vibration, electromagnetic interference, air pressure fluctuation and the like on IMU errors in an actual working environment is ignored. The existing calibration method has obvious limitation in coping with the dynamic coupling effect of multiple physical fields, so that the error compensation effect of calibration parameters obtained based on an ideal environment under actual complex working conditions is obviously reduced, and the IMU output generates obvious drift, so that the control precision and long-term stability of the whole inertial measurement unit are seriously weakened. In summary, in the prior art, because the IMU error calibration is generally performed in an ideal environment state, the complex coupling error caused by the multi-factor coupling effect is ignored, so that the compensation accuracy of the calibration parameters under the complex actual working condition is seriously reduced, and the output drift of the IMU is remarkably increased. Disclosure of Invention The application aims to provide an automatic calibration method and system for an inertial measurement unit and electronic equipment, which are used for solving the technical problems that in the prior art, IMU error calibration is usually carried out in an ideal environment state, complex coupling errors caused by a multi-factor coupling effect are ignored, compensation accuracy of calibration parameters under complex actual working conditions is seriously reduced, and IMU output drift is remarkably increased. In order to achieve the above purpose, the application provides an automatic calibration method and system of an inertial measurement unit and electronic equipment. The application provides an automatic calibration method of an inertial measurement unit, which is realized by an automatic calibration system of the inertial measurement unit, and comprises the steps of constructing an IMU multi-mode calibration environment, integrating a high-precision temperature and humidity control module, a vibration simulation device, an electromagnetic interference device and an air pressure control module, deploying a plurality of groups of reference sensors in the IMU multi-mode calibration environment, designing an IMU working environment test parameter table, driving the IMU multi-mode calibration environment according to the IMU working environment test parameter table to simulate an IMU to be calibrated, synchronously recording the IMU multi-mode test data and the multi-mode reference data of the plurality of groups of reference sensors, carrying out error source decomposition and quantization on the IMU multi-mode test data by combining the multi-mode reference data, constructing a multi-objective function, carrying out minimum solution on the IMU error parameter model based on the multi-objective function, determining objective parameters, and carrying out closed loop optimization on the IMU to be calibrated by the objective parameters. Optionally, defining IMU working environment factor information, wherein the IMU working environment factor information comprises temperature, humidity, vibration, electromagnetic interference and air pressure, analyzing a working application scene of the IMU to be calibrated according to the IMU working environment factor information to obtain an IMU working environment factor boundary, constructing a multi-mode parameter combination strategy, wherein the multi-mode parameter combination strategy comprises working scene coverage and test parameter gradient, and performing test parameter design on the IMU working environment factor boundary based on the multi-mode parameter combination strategy to generate an IMU working environmen