A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation
Abstract
:1. Introduction
2. Attitude Estimation Based on Complementary Filtering
2.1. Attitude Description
2.2. Attitude Estimation by Gyroscope
2.3. Attitude Estimation by Accelerometer/Magnetometer
2.4. Complementary Filtering Algorithm
3. Improved Algorithm for NCF
3.1. Proposed of First-Order Differential Data Processing Algorithm for Gyroscope
3.2. Design Adaptive Adjustment Strategy for Constants and Proposed of D-NCF
- Note the current measurements of the gyroscope, accelerometer, and magnetometer which are , , and , respectively.
- Depending on the and values calculated before, the gyroscope measurements are processed by the first-order differential data processing algorithm.
- The attitude angle is obtained by solving the dynamic differential equation according to the gyroscope measurements, and the attitude angle is obtained by using the triad algorithm according to the accelerometer and magnetometer measurements. Then, using the NCF algorithm to achieve the fusion of and , we get the comprehensive attitude angle .
- Calculate according to , and then update , to prepare for processing the next gyroscope measurement.
4. Experimental Verification of the D-NCF Algorithm
4.1. Experimental Setup
4.2. Experiment Results and Discussion
4.2.1. First-Order Differential Data Processing Algorithm for Gyroscope
4.2.2. Attitude Estimation Accuracy of D-NCF Algorithm
X2 = attitude angle (D-NCF)-attitude angle (EKF)M
4.2.3. Robustness of D-NCF Algorithm
4.3. Discussion of Experiment
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Experiment-IMU | UAV-IMU | ||
---|---|---|---|
accelerometers | Dynamic Range | ±4 g | ±16 g |
Digital Resolution | 0.244 mg/LSB | 0.122 mg/LSB | |
Noise Density | 90 | 90 | |
gyroscopes | Dynamic Range | ±500 deg/s | ±245 deg/s |
Digital Resolution | 8.75 mdps/LSB | 4.375 mdps/LSB | |
Noise Density | 9 | 7 | |
magnetometers | Dynamic Range | ±12 gauss | ±8 gauss |
Digital Resolution | 3421 LSB/gauss | 6842 LSB/gauss | |
Noise Density | 2 mGa | 2 mGa |
6 | 13 | |
8 | 9 |
NCF | D-NCF | |
---|---|---|
Roll | 1.1653 | 0.5093 |
Pitch | 2.9638 | 1.5542 |
Yaw | 0.9398 | 0.6827 |
Roll | Pitch | Yaw | |
---|---|---|---|
Z | 3.020 | −20.5024 | 4.6646 |
NCF | D-NCF | |
---|---|---|
1 | 0.0410 s | 0.0517 s |
2 | 0.0440 s | 0.0553 s |
3 | 0.0504 s | 0.0617 s |
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Wen, X.; Liu, C.; Huang, Z.; Su, S.; Guo, X.; Zuo, Z.; Qu, H. A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation. Sensors 2019, 19, 1340. https://doi.org/10.3390/s19061340
Wen X, Liu C, Huang Z, Su S, Guo X, Zuo Z, Qu H. A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation. Sensors. 2019; 19(6):1340. https://doi.org/10.3390/s19061340
Chicago/Turabian StyleWen, Xudong, Chunwu Liu, Zhiping Huang, Shaojing Su, Xiaojun Guo, Zhen Zuo, and Hao Qu. 2019. "A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation" Sensors 19, no. 6: 1340. https://doi.org/10.3390/s19061340
APA StyleWen, X., Liu, C., Huang, Z., Su, S., Guo, X., Zuo, Z., & Qu, H. (2019). A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation. Sensors, 19(6), 1340. https://doi.org/10.3390/s19061340