Navigation Sensor Fusion for Automatic Barometer Calibration
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Solution Overview
Problem
Existing navigation systems face challenges in providing accurate three-dimensional positioning, particularly altitude estimation, due to the limitations of GNSS technology in environments where satellite signals are unavailable or corrupted, and manual barometer calibration is cumbersome and not always feasible.
Innovation Solution
A method utilizing a data fusion process that integrates GNSS, IMU, and barometer data, employing a recursive estimation operation, specifically a Kalman filter, to automatically calibrate the barometer and provide accurate altitude estimation through a navigation device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual barometer calibration is performed by requiring user intervention, then calibration accuracy can be achieved, but ease of operation deteriorates and production costs increase due to dedicated testing procedures
Solution Approach 1:
The navigation device performs barometer calibration automatically without user intervention by using GNSS altitude measurements as reference. The system self-calibrates by comparing barometer readings with GNSS-derived altitude and adjusting calibration parameters accordingly, eliminating the need for manual user input while maintaining calibration accuracy
Solution Approach 2:
The system uses feedback from GNSS altitude measurements to continuously adjust and refine barometer calibration parameters. The calibration process incorporates feedback loops where barometer readings are compared with GNSS reference values, and calibration parameters are updated iteratively to improve accuracy without requiring manual intervention
2Measurement precision
If dedicated barometer calibration machinery is introduced in production, then calibration precision improves, but device complexity and production costs increase
Solution Approach 1:
The patent replaces mechanical calibration equipment with a software-based calibration algorithm that runs on the navigation device's processor. Instead of using physical calibration machinery, the system uses computational methods to process GNSS and barometer data, achieving calibration precision through software rather than hardware
Solution Approach 2:
The navigation device uses its existing GNSS receiver and processor for dual purposes: both navigation and barometer calibration. This multi-functionality eliminates the need for dedicated calibration equipment, as the same components serve multiple functions, thereby reducing device complexity and production costs while maintaining calibration precision
3Measurement precision
If GNSS technology is used for positioning, then absolute position reference is provided, but reliability deteriorates in environments where satellite signals are unavailable or corrupted
Solution Approach 1:
The system merges GNSS positioning with barometer-based altitude measurement to create a complementary navigation system. By combining the strengths of both technologies—GNSS providing absolute horizontal position and barometer providing continuous altitude measurement—the system achieves both high precision and reliability across diverse environments including GNSS-denied areas
Solution Approach 2:
The system dynamically changes the reliance between different measurement parameters based on environmental conditions. When GNSS signals are available, the system prioritizes GNSS data for horizontal positioning; when GNSS is unavailable or corrupted, the system switches to using barometer data for altitude measurement, thereby maintaining reliability through adaptive parameter selection
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 seamless and automatic altitude calibration without user intervention, ensuring continuous and accurate altitude information even in environments where GNSS is unavailable, reducing production costs and enhancing navigation system reliability.
Implementation Method 1
a barometer sensor providing a pressure measurement
Implementation Method 2
performing a recursive estimation operation, in particular a Kalman filtering, to obtain the altitude estimate including recursively estimating a state vector including state variables representing calibration parameters
Data Source
AI summary
A method for providing navigation information by a navigation sensing device including an absolute positioning source providing three-dimensional absolute position data including an absolute altitude value, an Inertial Measurement Unit providing inertial data, in particular accelerations and angular rates, and a barometer sensor providing a pressure measurement. The method includes processing the inertial data and the absolute position data to obtain two-dimensional position information, in particular longitude and latitude, and processing the pressure measurement and the absolute position data to obtain an altitude estimate.