Enhancing sensor accuracy in mobile multi-sensor systems for atmospheric monitoring using disturbance observer and sensor estimators
Year: 2025
Type: article
Abstract: Recent progress in marine environmental monitoring has underscored the importance of equally rigorous atmospheric observations, and it has consequently focused on developing mobile sensors that improve data collection accuracy and operational flexibility. unmanned aerial vehicles (UAVs) are attractive carriers owing to their low cost and operational agility; however, the stringent size–and–weight constraints imposed on onboard sensors often translate into poor accuracy, especially under rapidly fluctuating ambient temperatures. This paper introduces a compact, lightweight composite sensor payload – readily integrable with UAVs – that preserves measurement precision down to −40°C by embedding a disturbance observer (DOB)–based compensation algorithm directly in the sensor micro–controller, using externally sensed air temperature (via an insulated probe) as baseline data for onboard correction. The DOB continuously estimates and cancels temperature–induced bias and electromagnetic interference in real time, without hardware redundancy or external calibration during operation. High–altitude test–chamber experiments show that the proposed system lowers the temperature RMSE from 28.67°C to 15.74°C and raises the coefficient of determination ( R 2 ) from 0.02 to 0.76. These results confirm that DOB–assisted correction substantially enhances the robustness and reliability of lightweight UAV–compatible sensors, paving the way for high–resolution coastal–and–open–ocean ground–to–stratosphere profiling that supports coupled air–sea flux assessments for marine exploration.
Source: Frontiers in Marine Science
Authors: Shinhyung Kim, Abera Tullu, Sunghun Jung
Institution: Chosun University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,801
Awards: G207129595, G847345497
OpenAlex ID: W4415464689