UAV Position Control Using Filtered Barometric Altitude Data
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Solution Overview
Problem
Existing UAV control systems face challenges in accurately measuring altitude changes due to high accuracy errors in geolocation systems, especially in environments with obstructions or weather-related disturbances, leading to unstable flight operations.
Innovation Solution
Combining geolocation data with barometric pressure data and applying filtering techniques, such as complementary filters, to enhance altitude measurement accuracy and stabilize UAV position control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If geolocation data alone is used for altitude measurement, then the system complexity is low, but the measurement precision deteriorates due to high accuracy errors in geolocation systems
Solution Approach 1:
The patent combines geolocation data with barometric pressure data to determine altitude. The controller receives both types of sensor data and processes them together to calculate the UAV's position in three-dimensional space, thereby improving measurement precision while managing system complexity through integrated processing
Solution Approach 2:
The patent introduces filtering mechanisms as intermediaries between the raw sensor data and the final altitude calculation. The filter processor applies filtering techniques to both geolocation and barometric data before combining them, reducing measurement errors and stabilizing the altitude determination process
2Measurement precision
If filtering techniques are applied to sensor data, then the measurement precision improves, but the loss of time increases due to additional data processing
Solution Approach 1:
The patent applies filtering selectively based on data quality assessment. The filter processor evaluates the quality of incoming sensor data and applies filtering only when necessary to achieve the desired measurement precision, avoiding unnecessary processing time when data quality is already sufficient
Solution Approach 2:
The system performs self-assessment of data quality and automatically adjusts the filtering intensity. The controller monitors sensor data quality metrics and dynamically modifies the filtering process to maintain precision while minimizing processing time, allowing the system to serve itself without external intervention
3Reliability
If multiple sensor data sources are combined, then the reliability improves, but the device complexity increases due to additional sensors and processing mechanisms
Solution Approach 1:
The controller is designed with multi-functionality to handle both geolocation and barometric data processing. The same controller unit that manages basic UAV control also processes sensor data, filters information, and calculates three-dimensional position, thereby improving reliability without proportionally increasing device complexity
Solution Approach 2:
The system implements feedback mechanisms where the controller continuously monitors the quality and consistency of data from multiple sensors. Based on this feedback, the controller adjusts the weighting and processing of different data sources to maintain reliable position control while managing processing complexity through adaptive algorithms
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves altitude measurement accuracy by reducing errors, resulting in more stable and precise UAV positioning and operation, even in challenging environments.
Implementation Method 1
a second sensor that detects second sensor data based on a barometric pressure of an environment in which the controller is located
Data Source
AI summary
The present teachings provide a method. The method includes steps of determining a sensor data quality for sensor data detected by a sensor of a controller of an unmanned aerial vehicle. The method includes determining whether the sensor data quality satisfies a quality threshold. The method includes responsive to a determining that the sensor data quality satisfies the quality threshold, calculating a delta value by applying a window function of a smoothing window, the delta value representing a difference between an altitude measurement of first sensor data of the sensor data detected by the sensor of the controller and an altitude measurement of second sensor data of the sensor data detected by the sensor of the controller. The method includes outputting the delta value to determine a position of the controller in a three-dimensional space.