UAV Vector Sensor Calibration for Accurate In-Flight Navigation
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face navigation accuracy issues due to zero-point errors in vector sensors, which affect the precision of heading and posture measurements during flight.
Innovation Solution
A calibration method for UAV navigation that involves collecting current and previous measurement data from vector sensors, calculating an adjustment quantity to refine the correction value, and using this updated value to obtain more accurate valid data for controlling UAV headings and postures.
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 causing reduced measurement accuracy
Solution Approach 1:
The patent applies preliminary action by performing calibration operations before actual navigation measurements. The system collects calibration data when the UAV is stationary or in known positions, calculates correction values in advance, and stores these correction values for subsequent use during flight operations. This preliminary calibration process eliminates zero-point errors before they affect navigation accuracy.
Solution Approach 2:
The patent implements feedback by continuously monitoring measurement data from vector sensors and comparing it against expected values. When deviations are detected, the system adjusts correction values dynamically based on the feedback from actual flight performance and calibration data, creating a closed-loop system that maintains measurement accuracy throughout operation.
2Measurement precision
If manual calibration intervention is performed to correct zero-point errors, then measurement accuracy is improved, but operation complexity and time consumption increase
Solution Approach 1:
The patent applies self-service by enabling the UAV system to perform automatic calibration without manual intervention. The system autonomously collects calibration data, processes it through algorithms to determine correction values, and applies these corrections automatically. This self-calibrating capability eliminates the need for operators to manually adjust sensors while maintaining high measurement accuracy.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting correction values based on collected calibration data. The system modifies sensor output parameters automatically by applying calculated correction factors, transforming raw inaccurate data into calibrated accurate data through parameter transformation rather than manual physical adjustment.
3Reliability
If real-time calibration is performed during flight, then navigation accuracy is maintained dynamically, but computational complexity and processing time increase
Solution Approach 1:
The patent reduces real-time computational complexity by performing extensive calibration calculations before flight operations. Correction values are pre-computed based on calibration data collected during stationary phases or pre-flight procedures. During actual flight, the system only needs to apply these pre-computed corrections rather than performing full calibration algorithms in real-time, significantly reducing processing demands.
Solution Approach 2:
The patent applies partial action by performing complete calibration operations only when necessary (e.g., during stationary phases or pre-flight), and using simplified correction application during continuous flight. The system balances between thorough calibration and efficient real-time operation by applying partial calibration updates based on the flight phase and available computational resources.
Data Source
AI summary
This application discloses a calibration method for navigation of an UAV including a vector sensor. The calibration method includes: collecting, during a flight of the UAV, a current correction value and current data during a current measurement performed by the vector sensor; acquiring previous data during a previous measurement performed by the vector sensor; acquiring an adjustment quantity according to the current data and the previous data; acquiring a next correction value according to the current correction value and the adjustment quantity; and acquiring next original data during a next measurement performed by the vector sensor, acquiring next valid data according to the next original data and the next correction value, and controlling headings and postures of the UAV according to the next valid data. With the calibration method of this application, the next valid data Vk+1 more closely approximated to a true value can be obtained.