Hybridization Algorithms Optimize Onboard Classical and Quantum Accelerometers for Airborne Acceleration Measurements

The accurate measurement of acceleration is crucial for navigation and guidance systems, and researchers continually seek ways to improve these measurements by combining different sensor technologies. Benoit Kaczmarczuk, Yannick Bidel, and Alexandre Bresson, along with colleagues at their institutions, investigate two algorithms that merge data from a highly sensitive atom interferometer with a conventional classical accelerometer. Their work focuses on optimising how these sensors work together, and the team demonstrates a significant improvement in the correlation between the two accelerometer types, alongside a substantial reduction in errors when estimating the bias of the classical sensor. This advancement promises more precise and reliable inertial measurement units for a range of applications, including airborne navigation and potentially future quantum-enhanced guidance systems.

Hybrid Quantum Sensor Error Mitigation Techniques

Scientists have made significant progress in enhancing the performance of atom interferometry-based sensors by combining them with classical accelerometers. This hybrid approach aims to leverage the strengths of both technologies, achieving greater accuracy and stability in inertial measurements. Atom interferometry offers exceptional long-term precision, while classical sensors provide robustness and short-term stability. The research focuses on mitigating errors, particularly those caused by sensor rotation, to improve overall performance. A key challenge in atom interferometry is minimizing errors caused by the rotation of the sensor during operation.

The team employed advanced statistical analysis techniques, including Allan variance, to characterize sensor stability and noise. These methods allow for a precise evaluation of sensor performance and identification of potential error sources. The research also explores the potential for testing fundamental physics principles, such as the weak equivalence principle, with increased precision.

Airborne Sensing Enhanced by Atom Interferometry

Scientists have achieved significant advancements in hybrid inertial sensing by combining atom interferometry with classical accelerometers, demonstrating improved accuracy and stability in airborne measurements. The research focused on two hybridization algorithms, one extracting interferometer phase directly and the other employing a three-measurement combination technique, both designed to refine classical accelerometer data. Experiments conducted during a Greenland airborne campaign provided data for evaluating algorithm performance, specifically assessing bias and scale factor errors in the classical sensor. Initial tests revealed limitations in bias stability due to detection noise and uncorrelated acceleration at longer interferometer durations.

Further investigations incorporated rotational contributions, demonstrating a degradation of Allan standard deviation for durations exceeding a few milliseconds, caused by fluctuations in Coriolis accelerations. By implementing algorithms to estimate initial velocity and correct for Coriolis accelerations, scientists successfully restored Allan standard deviations to levels achieved in the initial tests. Even when accounting for realistic atomic temperature, inducing contrast loss, the team developed algorithms that maintained stability, achieving optimal performance around 4 milliseconds. Adapting the algorithms to account for fluctuating contrast during data processing yielded substantial improvements in stability for extended interferometer durations, approaching the levels of a gyrostabilized system with enhanced detection noise. Final tests, utilizing data from the Greenland campaign and simulating improved sensor quality, demonstrated the potential for a one order of magnitude improvement in stability, even in strapdown mode. These results highlight the possibility of enhancing measurement quality in challenging airborne environments and deliver a pathway towards more aggressive operating conditions for quantum sensors, opening new perspectives for airborne gravity measurement campaigns with improved performance.

Hybridization Improves Inertial Sensor Stability

The study highlights the potential for substantial improvements in sensor stability, potentially by an order of magnitude, even when operating in challenging conditions. By effectively integrating data from quantum and classical sensors, this work expands the operational range of quantum sensors and opens new possibilities for airborne gravity measurement campaigns, particularly in strapdown mode where enhanced performance is crucial. The authors acknowledge that further refinement of the algorithms could include dynamic correction of contrast noise, a factor currently not linearly related to the measured inertial quantity, contributing to even more robust performance in demanding operating environments.