Low-Cost High-Precision Barometric Measurement Using Sensor Arrays
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Solution Overview
Problem
Existing barometric pressure measurement systems are costly and lack precision, especially in applications requiring high accuracy like E911 services, where determining the altitude of a caller in a high-rise building is critical.
Innovation Solution
Employing multiple low-cost pressure sensors at known heights, optimizing individual sensor errors through a new error function, and integrating with a distributed fiber optic sensing (DFOS) system via acoustic modems to provide precise pressure readings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single high-cost sensor is used, then measurement precision is improved, but device cost increases
Solution Approach 1:
The system divides the measurement task across multiple low-cost pressure sensors (at least three sensors) positioned at different known heights, rather than relying on a single expensive sensor. Each sensor contributes to the overall measurement, and their individual errors are optimized through a new error function that incorporates known height differences, achieving high precision through collective measurement rather than single-point measurement.
Solution Approach 2:
Multiple low-cost pressure sensors are combined into a unified measurement system where their readings are integrated through a new error function. The system merges the data from multiple sensors with known positional relationships to produce a single high-precision barometric pressure measurement, effectively combining the capabilities of multiple inexpensive components to match or exceed a single expensive sensor.
2Measurement precision
If multiple sensors are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system assigns specific roles to sensors based on their local characteristics—each sensor's known height position becomes a unique quality attribute. The new error function utilizes these local height differences to optimize individual sensor contributions, where each sensor's specific positional information is leveraged to reduce overall measurement error rather than treating all sensors uniformly.
Solution Approach 2:
The system changes the parameter space by incorporating known height differences as additional constraints in the error function. Rather than simply averaging sensor readings, the error function optimizes measurements by considering the vertical separation between sensors, transforming the problem from a simple multi-sensor average to a height-weighted optimization that reduces complexity through physical constraints.
3Measurement precision
If sensors are positioned at different heights, then altitude determination accuracy is improved, but installation complexity increases
Solution Approach 1:
The known height positions of sensors are determined and recorded during the installation phase before actual barometric measurements begin. This preliminary establishment of vertical references simplifies subsequent measurements, as the height information is pre-established and only needs to be input once into the error function, rather than requiring continuous complex positioning during operation.
Data Source
AI summary
Disclosed are systems and methods to determine barometric pressure 1) using multiple low-cost pressure sensors located at known heights instead of a single high-cost sensor; 2) determines an actual pressure value—not by averaging multiple sensors but rather optimizing an expected error in each individual one of them and utilize their known sensor heights thereby defining a new error function; 3) our approach is scalable, i.e. the number of sensors can be increased, and multiple sensors can be grouped together into smaller cells such that each group of cell can be corrected separately, and can even be corrected among themselves. Finally, our systems and methods according to the present disclosure can advantageously be integrated with a distributed fiber optic sensing (DFOS) system via acoustic modems thereby providing extremely wide-area external, or interior buildings pressure readings.