UAV Vector Sensor Calibration for In-Flight Zero-Point Error Removal
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Solution Overview
Problem
UAV navigation accuracy is compromised by zero-point errors in vector sensors, which occur when the measured physical quantity is zero, leading to inaccurate heading and posture measurements.
Innovation Solution
A calibration method that involves collecting reference data during two measurements of a reference vector with known modulus, acquiring a zero-point offset, and using this offset to eliminate zero-point errors from original data, thereby obtaining valid data for accurate UAV navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vector sensors are used to measure headings and postures of the UAV, then navigation capability is provided, but zero-point errors occur when the to-be-measured physical quantity is zero, affecting navigation accuracy
Solution Approach 1:
The patent performs preliminary calibration actions before actual navigation measurements. The system collects reference data during two measurements of a reference vector with known modulus, calculates the zero-point offset M0 in advance, and stores it for subsequent use. This preliminary calibration eliminates zero-point errors before they affect navigation accuracy.
Solution Approach 2:
The patent replaces manual calibration mechanisms with an automated computational system. Instead of requiring physical adjustment or manual intervention to correct zero-point errors, the system uses processors to automatically calculate the zero-point offset M0 from reference data and apply it to correct original measurement data, substituting mechanical calibration with algorithmic correction.
2Measurement precision
If manual calibration is performed to eliminate zero-point errors, then measurement accuracy is improved, but operation complexity and time consumption increase
Solution Approach 1:
The system performs self-calibration without external intervention. The processor automatically collects reference data during flight, calculates the zero-point offset M0, and applies the correction to original data. This self-service mechanism eliminates the need for manual calibration operations, making the system easier to operate while maintaining high measurement accuracy.
Solution Approach 2:
The patent changes the operational parameters of the sensor system by introducing a dynamic correction parameter (the zero-point offset M0). Instead of requiring manual adjustment of sensor parameters, the system calculates and applies a correction offset that transforms the sensor output from inaccurate to accurate, simplifying the calibration process.
3Productivity
If calibration is performed during flight, then calibration efficiency is improved and manual intervention is eliminated, but the complexity of the calibration process increases
Solution Approach 1:
The calibration system is designed to be universal and multi-functional. The same processor that controls navigation also performs calibration functions. The reference vector measurement process serves dual purposes: it provides navigation data and simultaneously enables zero-point calibration. This multi-functionality increases calibration efficiency without proportionally increasing overall system complexity.
Solution Approach 2:
The patent introduces a reference vector as an intermediary element that facilitates calibration during flight. By measuring a known reference vector at different postures, the system creates an intermediate calibration state that bridges the gap between flight operations and accuracy correction. This intermediary approach enables efficient in-flight calibration while managing process complexity.
Data Source
AI summary
This application discloses a calibration method for navigation of an unmanned aerial vehicle (UAV), a non-transitory computer-readable storage medium and a UAV implementing the same. The calibration method includes: collecting, during a flight of the UAV, reference data during two measurements of a reference vector performed by a vector sensor; acquiring a zero-point offset M0 of the vector sensor according to the reference data; acquiring original data Rk of any vector measured by the vector sensor; acquiring valid data Vk according to the zero-point offset M0 and the original data Rk; and control headings and postures of the UAV according to the valid data Vk. With the calibration method in this application, the valid data Vk is defined as a vector data acquired after a zero-point error of the original data Rk is eliminated, which is more closely approximated to an actual value of a to-be-measured vector.