Passive Local Wind Estimator for UAVs
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Solution Overview
Problem
Nano Unmanned Aerial Vehicles (UAVs) face challenges in navigating local wind fields due to the absence of airspeed sensors, which are often omitted to reduce weight and complexity, making it difficult to measure airspeed and thus navigate with certainty.
Innovation Solution
A method and device that estimate airspeed based on acceleration and controlled aerodynamic forces, allowing the calculation of a wind field without direct airspeed measurement, using a model that incorporates rotation rate, control state, and drag coefficients to navigate the aircraft.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If airspeed sensors are installed to measure airspeed directly, then navigation precision is improved, but device complexity and weight increase
Solution Approach 1:
The patent replaces the mechanical airspeed sensor system with a computational model that calculates airspeed based on accelerometer data, control inputs, and aerodynamic equations. This substitution eliminates the need for complex pressure probe systems while maintaining airspeed measurement capability through software-based estimation.
Solution Approach 2:
The patent introduces an intermediary computational model that acts as a mediator between available sensor data (accelerometers, control inputs) and the required airspeed information. This model uses aerodynamic equations to bridge the gap between measured quantities and the desired airspeed parameter without requiring direct airspeed sensing.
2Reliability
If airspeed sensors are installed to measure airspeed directly, then navigation reliability is improved, but weight increases
Solution Approach 1:
The patent replaces physical airspeed sensing hardware with a software-based computational approach using existing onboard sensors. This substitution significantly reduces the weight penalty associated with traditional airspeed sensors while maintaining navigation reliability through accurate aerodynamic modeling and continuous calculation.
Solution Approach 2:
The aircraft uses its own existing sensors (accelerometers) and control system data to generate airspeed information independently, without requiring external airspeed sensing equipment. The system serves its own navigation needs by computing airspeed from internally available measurements and aerodynamic principles.
3Measurement precision
If airspeed sensors are installed to measure airspeed directly, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces expensive airspeed sensor hardware with a software-based solution that utilizes already-present onboard systems. This substitution eliminates the need for additional costly components while achieving comparable or superior measurement precision through computational methods and aerodynamic modeling.
Solution Approach 2:
The patent creates a computational copy of airspeed measurement functionality using software algorithms rather than physical sensors. This virtual copy replicates the measurement capability without requiring expensive hardware, reducing manufacturing costs while maintaining measurement accuracy through mathematical modeling.
4Device complexity
If airspeed sensors are omitted to reduce weight, then device complexity is reduced, but airspeed measurement capability is lost
Solution Approach 1:
The patent replaces the need for physical airspeed sensors with a computational system that derives airspeed information from accelerometer data and aerodynamic models. This substitution maintains airspeed measurement capability without the complexity of traditional sensing systems, as the information is generated through calculation rather than direct measurement.
Solution Approach 2:
The computational model serves as an intermediary that reconstructs airspeed information from alternative measurements. Rather than directly measuring airspeed, the system uses accelerometers and aerodynamic equations as intermediaries to infer airspeed, preventing information loss while avoiding complex sensor systems.
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
Enables accurate estimation and display of local wind speed and direction, allowing the UAV to be positioned advantageously relative to the wind, reducing errors and system complexity while eliminating the need for airspeed sensors, thus reducing weight and cost.
Implementation Method 1
The aircraft obtains information about its ground speed by using a combination of its GPS and inertial sensors
Implementation Method 2
The device estimates an airspeed of the aircraft based on an acceleration aB of the aircraft and controlled aerodynamic forces applied to the aircraft
Implementation Method 3
The device estimates an airspeed of the aircraft based on an acceleration aB of the aircraft and controlled aerodynamic forces applied to the aircraft
Implementation Method 4
The device estimates a wind field experienced by the aircraft based on the ground speed and the airspeed
Data Source
AI summary
Local wind fields can be predicted if both the airspeed and the ground speed of the helicopter are known. An aircraft that uses an inertial navigation unit, autopilot and estimator allows a measure of ground speed to be known with good certainty. The embodiments herein extends this system to allow an estimate of the local wind field to be found without actively using an airspeed sensor, but instead combining the measurements of an accelerometer and a drag force model and a model of controlled aerodynamics of the aircraft to estimate the airspeed, which again can be used to estimate the local wind speed.