An IMU system error calibration device and calibration method

Abstract

This invention provides an IMU system error calibration device and method, belonging to the field of inertial measurement unit error calibration technology. The device includes an optical platform with a perforated aluminum plate, an adapter plate, and an R-axis displacement platform, all fixed from bottom to top with screws. The IMU is fixed to the R-axis displacement platform. The method utilizes the above device to perform multi-position static and multi-position rotational data acquisition, obtaining static data of the IMU at different attitudes and rotational positions. This data is then substituted into the IMU system error equation, and a nonlinear optimization algorithm is used to inversely calculate the optimal system error parameters, such as zero-bias error, scaling factor error, and installation error. This invention employs the above-mentioned IMU system error calibration device and method, which eliminates the need for high-precision equipment, is simple to operate, low in cost, and effectively improves IMU measurement accuracy, making it suitable for practical scenarios.

Description

Technical Field

[0001] This invention relates to the field of inertial measurement unit error calibration technology, and in particular to an IMU system error calibration device and calibration method. Background Technology

[0002] In the field of inertial navigation, the inertial measurement unit (IMU) is a core component, and its measurement accuracy directly affects the performance of the navigation system. However, during the manufacturing process of the IMU, due to factors such as process technology and assembly, systematic errors such as zero bias error, scaling factor error, and installation error are inevitably generated. These errors will seriously affect the measurement accuracy of the IMU and the positioning accuracy of the navigation system.

[0003] For ultra-low-cost IMUs, while hardware costs are lower, manufacturing processes and precision control are correspondingly weaker, making systematic errors more prominent. Ultra-low-cost IMUs are typically used in cost-sensitive applications such as consumer electronics, small drones, and low-cost navigation devices. In these scenarios, although the accuracy requirements are lower than for mid-to-high-end IMUs, sufficient accuracy is still needed to meet basic navigation and measurement needs. Therefore, systematic error calibration is a crucial step in improving the measurement accuracy of ultra-low-cost IMUs.

[0004] Traditional IMU error calibration methods typically rely on high-precision turntables and calibration equipment. These devices are expensive, bulky, and complex to operate, making them unsuitable for ultra-low-cost IMU applications. Furthermore, traditional methods often require consideration of complex factors such as the Earth's rotation during calibration, further increasing the difficulty and cost. For ultra-low-cost IMUs, these high-precision devices and complex calibration procedures are not only unnecessary but also significantly increase costs, negating their cost advantage.

[0005] Another characteristic of ultra-low-cost IMUs is their relatively unstable error characteristics. Due to hardware cost limitations, the performance and stability of their internal components may not be as good as those of mid-to-high-end IMUs, leading to significant variations in error under different environments and usage conditions. Therefore, a method for rapid and simple field calibration is needed to accommodate their unstable error characteristics. Furthermore, the application scenarios for ultra-low-cost IMUs typically place high demands on real-time performance and convenience; the calibration process needs to be as simple and fast as possible to minimize the impact on equipment use. Summary of the Invention

[0006] The purpose of this invention is to provide an IMU system error calibration device and calibration method that does not require high-precision equipment, is easy to operate, low in cost, and can effectively improve the IMU measurement accuracy, making it suitable for practical scenarios.

[0007] To achieve the above objectives, the present invention provides an IMU system error calibration device, including an optical platform with a porous aluminum plate, an adapter plate, and an R-axis displacement platform;

[0008] The optical platform, the perforated aluminum plate, the adapter plate, and the R-axis displacement platform are arranged vertically from bottom to top, and adjacent components are fixed by screws. The IMU is detachably fixed to the top of the R-axis displacement platform.

[0009] The optical platform has a rectangular plate structure with a first mounting hole at each of its four corners. The first mounting hole is used to connect to the external support platform to achieve a stable installation of the optical platform. The optical platform also has multiple sets of second mounting holes arranged at equal intervals along the horizontal direction on its surface. The second mounting holes are used to fit with screws through the adapter plate, and the inner diameter of the first mounting hole is larger than that of the second mounting hole.

[0010] The adapter plate is a rectangular structure adapted to the perforated aluminum plate of the optical platform. It has two sets of mounting holes on its surface, namely the third mounting hole and the fourth mounting hole. The diameter of the third mounting hole matches the second mounting hole on the perforated aluminum plate of the optical platform and is used to connect with the perforated aluminum plate of the optical platform by screws. The fourth mounting hole is used to cooperate with the R-axis displacement platform by screws.

[0011] The R-axis displacement platform includes a rotating base, a fine-tuning knob, and a large-adjustment knob. An IMU mounting hole is provided at the center of the rotating base for embedding and fixing the IMU. A fifth mounting hole is provided at each of the four corners of the rotating base. The diameter of the fifth mounting hole is equal to that of the fourth mounting hole on the adapter plate, and it is used to fix the adapter plate with screws. The fine-tuning knob and the large-adjustment knob are respectively located on the side of the rotating base, and are used to realize small-angle precision adjustment and large-angle rapid adjustment of the rotating base, respectively.

[0012] The present invention also provides an IMU system error calibration method, which uses the above-mentioned IMU system error calibration device and includes the following steps:

[0013] Step S1: Fix the IMU on the R-axis displacement platform, and provide support through the porous aluminum plate of the optical platform. Use the R-axis displacement platform to realize the attitude adjustment and rotation operation of the IMU. Acquire data of the IMU in different attitudes and rotation positions through multi-position static acquisition and multi-position rotation acquisition.

[0014] Step S2: Input the data obtained in step S1 into the error model and use the optimization algorithm to find the optimal system error parameters. The system error parameters include zero bias error, scaling factor error and installation error.

[0015] Preferably, the multi-position static acquisition involves statically acquiring data from the IMU in the following orientations: X-axis up, X-axis down, Y-axis up, Y-axis down, Z-axis up, and Z-axis down. Each orientation is acquired for 60 seconds, and each orientation is repeated 3 times.

[0016] Preferably, the multi-position rotation acquisition uses an R-axis displacement platform to rotate the IMU, keeping it stationary for 10 seconds after each 90° rotation, until it completes one full rotation.

[0017] Preferably, step S2 specifically includes: establishing an error model containing zero bias, scaling factor, and non-orthogonality parameters based on IMU data obtained from static acquisition and rotation acquisition, and constructing a residual function between the measured values ​​and the ideal output of the model; iteratively optimizing the system error parameters using the Levenberg-Marquardt algorithm to minimize the sum of squared residuals, and outputting the optimized calibration parameters for real-time compensation of IMU measurement data.

[0018] The preferred error model is as follows:

[0019] ;

[0020] ;

[0021] in, These represent the ideal values ​​of the x, y, and z axes of the accelerometer. These represent the ideal values ​​of the x, y, and z axes of the gyroscope. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. , , These represent the deviations of the speedometer's x, y, and z axis coordinate measurements, respectively. , , These represent the deviations of the x, y, and z axis coordinate measurements of the gyroscope.

[0022] Preferably, the accelerometer residual vector as follows:

[0023] ;

[0024] Gyroscope residual vector as follows:

[0025] ;

[0026] in, , , They represent the first The true ideal values ​​of the accelerometer's x, y, and z axes in the dataset. , , They represent the first The ideal values ​​of the x, y, and z axes in the dataset. , , They represent the first In this set of data, the true ideal values ​​of the gyroscope's x, y, and z axes are... , , They represent the first Ideal values ​​for the xyz axes of the gyroscope in the dataset.

[0027] The preferred optimization objective of the Levenberg-Marquardt algorithm is... as follows:

[0028] ;

[0029] in, This indicates the total number of data sets collected in the calibration experiment. This indicates transpose.

[0030] Therefore, the present invention employs the above-described IMU system error calibration device and calibration method, and the beneficial technical effects are as follows:

[0031] (1) In terms of the device, it consists of an optical platform with a multi-hole aluminum plate, an adapter plate and an R-axis displacement platform. It has a simple structure and low cost, which is suitable for the low-cost application requirements of IMU. The rotation accuracy of the R-axis displacement platform is 0.03°. The specific hole design of the adapter plate can meet the basic accuracy requirements of IMU for multi-position static and rotational data acquisition. No high-precision turntable is required, which reduces the calibration cost.

[0032] (2) In terms of method, the parameters such as static acquisition for 60 seconds and rotation of 90° and stay for 10 seconds are set. In view of the characteristics of IMU error instability and the need for rapid on-site calibration, multiple sets of data acquisition combined with LM algorithm can effectively solve its zero bias, scale factor and installation error, and improve measurement accuracy. These designs are not necessary for medium and high precision IMUs, highlighting the advantages of targeted adaptation to IMU. Attached Figure Description

[0033] Figure 1 This is a structural diagram of an IMU system error calibration device according to the present invention;

[0034] Figure 2 Raw data from the accelerometer and gyroscope are collected while stationary with the Z-axis pointing upwards.

[0035] Figure 3 The raw data from the accelerometer and gyroscope are obtained by rotating one revolution upwards along the Z-axis.

[0036] Figure Labels

[0037] 1. Perforated aluminum plate for optical platform; 2. Adapter plate; 3. R-axis displacement platform; 301. Rotating base; 302. Fine adjustment knob; 303. Large adjustment knob; 4. First mounting hole; 5. Second mounting hole; 6. Third mounting hole; 7. Fourth mounting hole; 8. IMU mounting hole; 9. Fifth mounting hole. Detailed Implementation

[0038] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0039] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0040] Example 1

[0041] like Figure 1 As shown, an IMU system error calibration device includes an optical platform with a porous aluminum plate 1, an adapter plate 2, and an R-axis displacement platform 3.

[0042] The optical platform, the porous aluminum plate 1, the adapter plate 2, and the R-axis displacement platform 3 are arranged vertically from bottom to top, and adjacent components are fixed by screws. The IMU is detachably fixed to the top of the R-axis displacement platform.

[0043] The optical platform porous aluminum plate 1 has a rectangular plate structure, with a first mounting hole 4 opened in each of its four corner areas. The first mounting hole 4 is used to connect to the external support platform to achieve a stable installation of the optical platform porous aluminum plate 1. The optical platform porous aluminum plate 1 also has multiple sets of second mounting holes 5 arranged at equal intervals in the horizontal direction. The second mounting holes 5 are used to cooperate with the adapter plate 2 by screws, and the inner diameter of the first mounting hole 4 is larger than the inner diameter of the second mounting hole 5.

[0044] The porous aluminum plate 1 of the optical platform is made of low-cost, lightweight materials, offering excellent mechanical stability and heat dissipation, making it suitable for IMU applications. Its porous design allows for flexible adjustment of the IMU's mounting position, ensuring stable fixation in various orientations while reducing material usage and further lowering costs. The porous aluminum plate provides a stable support base, guaranteeing the reliability of the calibration process even with the use of low-cost materials.

[0045] The adapter plate 2 is a rectangular structure adapted to the porous aluminum plate 1 of the optical platform. Two sets of mounting holes are provided on its surface, namely the third mounting hole 6 and the fourth mounting hole 7. The diameter of the third mounting hole 6 matches the second mounting hole 5 on the porous aluminum plate 1 of the optical platform, and is used to connect with the porous aluminum plate 1 of the optical platform by passing screws through it. The fourth mounting hole 7 is used to cooperate with the R-axis displacement platform 3 by passing screws through it.

[0046] The adapter plate 2 connects the perforated aluminum plate 1 of the optical platform and the R-axis displacement platform 3, ensuring a secure connection between the three components. Its design takes into account the size and installation requirements of the IMU, offering a variety of hole options to accommodate different IMU models. The adapter plate employs a simple mechanical structure and low-cost materials, such as aluminum alloy or engineering plastics, ensuring functionality while controlling costs. The specific hole design of the adapter plate, combined with the rotational accuracy of the R-axis displacement platform 3, meets the basic accuracy requirements of the IMU for multi-position static and rotational data acquisition, eliminating the need for a high-precision turntable.

[0047] The R-axis displacement platform 3 includes a rotating base 301, a fine-tuning knob 302, and a large-adjustment knob 303. An IMU mounting hole is provided at the center of the rotating base 301 for embedding and fixing an IMU. A fifth mounting hole 9 is provided at each of the four corners of the rotating base 301. The diameter of the fifth mounting hole 9 is equal to the diameter of the fourth mounting hole 7 on the adapter plate 2, and is used to fix it to the adapter plate 2 by passing screws through it. The fine-tuning knob 302 and the large-adjustment knob 303 are respectively provided on the side of the rotating base 301, and are used to realize small-angle precision adjustment and large-angle rapid adjustment of the rotating base, respectively.

[0048] The R-axis displacement platform 3 has a rotational accuracy of 0.03°. While this level of accuracy is not as high as that of a high-precision rotary table, it is sufficient for the IMU and meets its error calibration requirements. The R-axis displacement platform 3 is easy to operate; precise rotational control can be achieved through fine-tuning knobs, making it suitable for scenarios requiring rapid on-site calibration. The cost of the R-axis displacement platform 3 is significantly lower than that of a high-precision rotary table, and its simple structure makes it easy to maintain and use, aligning with the application scenarios of IMUs.

[0049] Therefore, the IMU system error calibration device of the present invention has been optimized for the characteristics of IMU in terms of material selection, structural design and operation process, ensuring low cost, high efficiency and ease of operation, effectively improving the measurement accuracy of IMU and suitable for practical application scenarios.

[0050] This embodiment uses the WT9011DCL-bt50 IMU, which integrates a three-axis accelerometer and a gyroscope. Its factory-calibrated performance indicators are shown in Table 1.

[0051] Table 1 IMU Factory Calibration Performance Indicators

[0052]

[0053] The IMU is fixed to the R-axis displacement platform for data acquisition:

[0054] Static data acquisition: The IMU was fixed in six different orientations: X-axis up, X-axis down, Y-axis up, Y-axis down, Z-axis up, and Z-axis down. For each orientation, 60 seconds of static data acquisition was performed on three axes, resulting in a total of 18 sets of static data. The raw accelerometer and gyroscope data are shown below. Figure 2 As shown, the X, Y, and Z axes are represented by red, green, and blue, respectively.

[0055] Rotational data acquisition: Keeping the IMU fixed to the R-axis displacement platform, rotate the IMU 90° at a time using the fine-tuning knob, hold for 10 seconds, and then acquire data. Repeat this process until a 360° rotation is completed, recording static data at different positions during the rotation. This process is repeated three times to obtain 18 sets of rotational data. The raw data for the three-axis acceleration and angular velocity are as follows: Figure 3 As shown.

[0056] The collected data is fed into the error model, and a residual function is constructed between the measured values ​​and the ideal output of the model.

[0057] The error model is as follows:

[0058] ;

[0059] ;

[0060] in, These represent the ideal values ​​of the x, y, and z axes of the accelerometer. These represent the ideal values ​​of the x, y, and z axes of the gyroscope. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. , , These represent the deviations of the speedometer's x, y, and z axis coordinate measurements, respectively. , , These represent the deviations of the x, y, and z axis coordinate measurements of the gyroscope.

[0061] Accelerometer residual vector as follows:

[0062] ;

[0063] Gyroscope residual vector as follows:

[0064] ;

[0065] in, , , They represent the first The true ideal values ​​of the accelerometer's x, y, and z axes in the dataset. , , They represent the first The ideal values ​​of the x, y, and z axes in the dataset. , , They represent the first In this set of data, the true ideal values ​​of the gyroscope's x, y, and z axes are... , , They represent the first Ideal values ​​for the xyz axes of the gyroscope in the dataset.

[0066] The optimization objective of the Levenberg-Marquardt algorithm as follows:

[0067] ;

[0068] in, This indicates the total number of data sets collected in the calibration experiment. This indicates transpose.

[0069] The error parameters and corresponding standard deviations of the accelerometer and gyroscope were obtained by iteratively solving the problem using the Levenberg-Marquardt (LM) method, as shown in Tables 2 and 3. The accelerometer exhibited the largest Z-axis deviation and poorest stability. During horizontal rotation, even slight vibrations caused significant fluctuations in the Z-axis output, with a peak value reaching 11.8 m / s². 2 The Z-axis offset of the gyroscope is relatively low compared to the other two axes. When the IMU is placed at the foot of a pedestrian, pointing the Z-axis towards the sky helps to reduce heading errors in navigation tasks.

[0070] Table 2. Average calibration values ​​and standard deviations of accelerometer error parameters

[0071]

[0072] Table 3. Average calibration values ​​and standard deviations of gyroscope error parameters

[0073]

[0074] in, This indicates the accelerometer's orthogonal error. This indicates the proportional error of the accelerometer. This indicates the zero bias error of the accelerometer. This represents the gyroscope's orthogonality error. This indicates the proportional error of the gyroscope. This indicates the zero bias error of the gyroscope.

[0075] It is worth noting that all contents not described in detail in this invention are existing technologies and are well known to those skilled in the art.

[0076] Therefore, the present invention employs the above-mentioned IMU system error calibration device and calibration method, which does not require high-precision equipment, is easy to operate, low in cost, and can effectively improve the IMU measurement accuracy, making it suitable for practical scenarios.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An IMU system error calibration device, characterized in that, This includes a porous aluminum plate for the optical platform, an adapter plate, and an R-axis displacement platform; The optical platform, the perforated aluminum plate, the adapter plate, and the R-axis displacement platform are arranged vertically from bottom to top, and adjacent components are fixed by screws. The IMU is detachably fixed to the top of the R-axis displacement platform. The optical platform has a rectangular plate structure with a first mounting hole at each of its four corners. The first mounting hole is used to connect to the external support platform to achieve a stable installation of the optical platform. The optical platform also has multiple sets of second mounting holes arranged at equal intervals along the horizontal direction on its surface. The second mounting holes are used to fit with screws through the adapter plate, and the inner diameter of the first mounting hole is larger than that of the second mounting hole. The adapter plate is a rectangular structure adapted to the perforated aluminum plate of the optical platform. It has two sets of mounting holes on its surface, namely the third mounting hole and the fourth mounting hole. The diameter of the third mounting hole matches the second mounting hole on the perforated aluminum plate of the optical platform and is used to connect with the perforated aluminum plate of the optical platform by screws. The fourth mounting hole is used to cooperate with the R-axis displacement platform by screws. The R-axis displacement platform includes a rotating base, a fine-tuning knob, and a large-tuning knob. An IMU mounting hole is provided at the center of the rotating base for embedding and fixing the IMU. A fifth mounting hole is provided at each of the four corners of the rotating base. The diameter of the fifth mounting hole is equal to that of the fourth mounting hole on the adapter plate, and it is used to fix the IMU to the adapter plate by passing screws through it. The fine-tuning knob and the large-tuning knob are respectively located on the side of the rotating base. The method applied to the aforementioned IMU system error calibration device includes the following steps: Step S1: Fix the IMU on the R-axis displacement platform, and provide support through the porous aluminum plate of the optical platform. Use the R-axis displacement platform to realize the attitude adjustment and rotation operation of the IMU. Acquire data of the IMU in different attitudes and rotation positions through multi-position static acquisition and multi-position rotation acquisition. Step S2: Input the data obtained in step S1 into the error model and use the optimization algorithm to find the optimal system error parameters. The system error parameters include zero bias error, scaling factor error and installation error. Multi-position static acquisition involves statically acquiring data from the IMU in the following orientations: X-axis up, X-axis down, Y-axis up, Y-axis down, Z-axis up, and Z-axis down. Each orientation is acquired for 60 seconds, and each orientation is repeated 3 times. Multi-position rotation acquisition uses an R-axis displacement platform to rotate the IMU, holding it still for 10 seconds after each 90° rotation, until it completes one full rotation.

2. The IMU system error calibration device according to claim 1, characterized in that, Step S2 specifically includes: establishing an error model containing zero bias, scaling factor, and non-orthogonality parameters based on IMU data obtained from static acquisition and rotation acquisition, and constructing a residual function between the measured values ​​and the ideal output of the model; iteratively optimizing the system error parameters using the Levenberg-Marquardt algorithm to minimize the sum of squared residuals, and outputting the optimized calibration parameters for real-time compensation of IMU measurement data.

3. The IMU system error calibration device according to claim 2, characterized in that, The error model is as follows: ； ； in, These represent the ideal values ​​of the x, y, and z axes of the accelerometer. These represent the ideal values ​​of the x, y, and z axes of the gyroscope. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. These represent the measured values ​​of the accelerometer's x, y, and z axes, respectively. , , These represent the deviations of the speedometer's x, y, and z axis coordinate measurements, respectively. , , These represent the deviations of the x, y, and z axis coordinate measurements of the gyroscope.

4. The IMU system error calibration device according to claim 2, characterized in that, Accelerometer residual vector as follows: ； Gyroscope residual vector as follows: ； in, , , They represent the first The true ideal values ​​of the accelerometer's x, y, and z axes in the dataset. , , They represent the first The ideal values ​​of the x, y, and z axes in the dataset. , , They represent the first In this set of data, the true ideal values ​​of the gyroscope's x, y, and z axes are... , , They represent the first Ideal values ​​for the xyz axes of the gyroscope in the dataset.

5. The IMU system error calibration device according to claim 2, characterized in that, The optimization objective of the Levenberg-Marquardt algorithm as follows: ； in, This indicates the total number of data sets collected in the calibration experiment. This indicates transpose.

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