#aqnav

Acubed and SandboxAQ Announce Aviation Safety Magnetic Navigation Advances

SandboxAQ and Acubed, Airbus' Silicon Valley research centre, have made significant quantum magnetic navigation (MagNav) advances, enhancing aircraft safety and resilience. These advances, which centre on their AI-powered AQNav system, will usher in a new era of intelligent automation in the sky by protecting against GNSS denial, jamming, and spoofing.

Critical global challenge addressed

GNSS disruptions can threaten flight operations and safety worldwide, rendering aviation more vulnerable. AQNav's rigorous R&D is driven by this critical concern. The quantum sensors of AQNav were developed in 2021 by quantum technology leader SandboxAQ. The technology has garnered notice as one of TIME's Best Inventions of 2024 and ACT-IAC's 2025 Innovations Champion Award.

Precision quantum magnetometers allow AQNav to “read” Earth's crustal magnetic anomalies like a geophysical fingerprint. It uses Large Quantitative Models (LQMs) to efficiently reduce electromagnetic interference to locate aircraft locations without satellite signals for accuracy.

Thorough Testing and Unmatched Accuracy

SandboxAQ has collaborated with U.S. AQNav will be thoroughly tested and improved by the USAF and partners. After demonstrating real-time navigation skills during USAF flight testing last July, the technology was admitted into the 2025 NATO DIANA cohort to improve its capabilities.

Today, a nationwide project with Acubed's Flight Lab to assess AQNav's navigational accuracy revealed noteworthy discoveries. Goals included testing magnetic anomaly-aided navigation against the aviation industry's demanding Required Navigation Performance (RNP) standards. These requirements are necessary for military, commercial, and passenger aircraft to use the system.

Even on extended flights, AQNav excelled en route accuracy between airports, proving its outstanding precision in tests. Flight data was collected, reprocessed, and streamed in real time to ensure system viability in real-world operations. This supplied useful statistics for team evaluation.

Real-World Robustness

The operational realism in their design distinguishes these test results. Acubed and SandboxAQ created tests to simulate the “noisy, messy, and unpredictable environments real pilots face every day,” said Elijha Williams, AQNav's technical engagement manager. The highlights of these strong testing were:

A publicly available Beechcraft Baron 58 was used to test AQNav instead of a geosurvey platform. AQNav instrumentation was integrated with minimal aircraft modification, avoiding electromagnetic shielding and noise isolation. AQNav's software kept a clean magnetic signal despite internal interference, and all sensors were strategically located throughout the aircraft. For all flights across the US, Canada, Mexico, and oceans, researchers used the North American Magnetic Anomaly Map (NAMAM). Flight operations included more than 200 continental US airports on a range of operationally critical routes. Importantly, not filtering routes by favourable geomagnetic gradients, map quality, or magnetic anomaly strength tested the system's adaptability. Over 150 flying hours were recorded. Diverse Geophysical Environments: Data was collected from sparsely populated plains to magnetically rich mountainous regions to adequately depict the diverse geographies where aeroplanes operate without GNSS. Genuine Operational Noise Handling: AQNav effectively removed aircraft-generated electromagnetic, vibrational, and other airframe-induced noise. AQNav always outperformed the INS without GNSS in test flights over two hours. AQNav achieved its highest accuracy of less than 74 meters, or two-thirds the length of an American football pitch, during a one-hour flight over tough mountainous and forested terrain in California.

AQNav Sandbox

SandboxAQ, the first dual-use magnetic navigation system, sends real-time positioning data to U.S. iPads. US Air Force aircraft. It has a unique roll-on/roll-off feature that offers live position information during uncontrolled, operational flights.

In 2023, the USAF awarded SandboxAQ a Direct-to-Phase-II Small Business Innovation Research contract to study magnetic anomaly navigation. It completed the AQNav system's initial flight tests eight months early. It contains the largest public Magnetic Navigation database. AQNav has flown 40 missions and 200 hours in four aircraft, from single-engine commercial planes to massive military transports. More flight testing are coming.

In addition to the USAF, Airbus' Silicon Valley R&D centre, Boeing, and other allies are interested in AQNav. The companies are assessing the technology at various phases.

How AQNav Works

AQNav uses sensitive quantum magnetometers to collect data from Earth's crustal magnetic field, which has immutable patterns like human fingerprints and is spatially different.

Comparing this data with magnetic maps utilising unique AI algorithms lets the machine locate itself quickly and accurately. Because quantum sensors are sensitive, AI algorithms boost the signal-to-noise ratio and minimise mechanical, electrical, and other interference that could impair the system's position determination.

Unjammable/Unspoofable Worldwide Signal: Earth's crustal magnetic field is everywhere and provides unfettered access and a dependable signal. AQNav works well as a supplement to other navigation systems because it is weather- and lighting-independent. land Agnostic: AQNav can navigate in the air, over open sea, on distant land, underwater, and underground without visual ground characteristics. Passive Technology: AQNav passively receives geomagnetic data without emitting or reflecting signals to reduce vehicle detection. Flexible, Adaptable Technology: AQNav functions at room temperature without shielding and can be fitted into single-engine and multi-engine airliners. Seamless Integration: AQNav can interface with inertial, visual, satellite, and other cutting-edge navigation systems to create a “system of systems” for safe and precise navigation. See also Density Matrix Embedding Theory & SQD for Quantum Modelling.

Setting the Stage for GNSS Independence

Due to this big effort, aviation has adopted AQNav more. By maintaining accuracy in an uncontrolled, unfiltered national testbed, SandboxAQ has shown AQNav's viability and operational robustness.

Andrew Sosa Sosanya, SandboxAQ's quantum navigation machine learning engineer, says the “highly relevant MagNav dataset” has a “flywheel effect: the more data it collects, the faster it improves model accuracy across diverse mission profiles,” emphasising its strategic value.

Our advertising showed AQNav's scalability, which is vital to the aviation industry's future, and its impressive performance metrics. Single-flight demos are important proofs of concept, but “scaling is where real progress happens,” the source said. Acubed's Flight Lab's large-scale data collection and analysis accelerated development and validation. This agile platform greatly enhances data collection in actual operating scenarios, accelerating technology maturity and global performance insights.

“AQNav’s recent results have been greatly aided by the relationship with Acubed,” said SandboxAQ staff systems engineer Eddie Rodriguez. It improved navigation accuracy, sped up hardware and software iterations, and characterised aircraft electromagnetic interference noise profiles enabling flight planning improvements and fast feedback loops. Acubed's adaptability in ground tests and EMI surveys “enriched the data pool significantly, pushing the boundaries of sensor placement and denoising capabilities for the next-gen devices,” said SandboxAQ embedded systems engineer Saurabh Kuruvila.

SandboxAQ and its partners are moving aviation closer to a future where GNSS is just one of many accurate navigation systems, rather than a single point of failure that might threaten lives and disrupt crucial military and commercial operations with each hour and sortie flown. Acubed and SandboxAQ Announce Groundbreaking Magnetic Navigation for Aviation Safety. Continued cooperation with government and commercial partners is speeding up MagNav system rollout.

SandboxAQ and Acubed, Airbus' Silicon Valley research centre, have made significant quantum magnetic navigation (MagNav) advances, enhancing aircraft safety and resilience. These advances, which centre on their AI-powered AQNav system, will usher in a new era of intelligent automation in the sky by protecting against GNSS denial, jamming, and spoofing.

Critical global challenge addressed GNSS disruptions can threaten flight operations and safety worldwide, rendering aviation more vulnerable. AQNav's rigorous R&D is driven by this critical concern. The quantum sensors of AQNav were developed in 2021 by quantum technology leader SandboxAQ. The technology has garnered notice as one of TIME's Best Inventions of 2024 and ACT-IAC's 2025 Innovations Champion Award.

Precision quantum magnetometers allow AQNav to “read” Earth's crustal magnetic anomalies like a geophysical fingerprint. It uses Large Quantitative Models (LQMs) to efficiently reduce electromagnetic interference to locate aircraft locations without satellite signals for accuracy.

Thorough Testing and Unmatched Accuracy SandboxAQ has collaborated with U.S. AQNav will be thoroughly tested and improved by the USAF and partners. After demonstrating real-time navigation skills during USAF flight testing last July, the technology was admitted into the 2025 NATO DIANA cohort to improve its capabilities.

Today, a nationwide project with Acubed's Flight Lab to assess AQNav's navigational accuracy revealed noteworthy discoveries. Goals included testing magnetic anomaly-aided navigation against the aviation industry's demanding Required Navigation Performance (RNP) standards. These requirements are necessary for military, commercial, and passenger aircraft to use the system.

Even on extended flights, AQNav excelled en route accuracy between airports, proving its outstanding precision in tests. Flight data was collected, reprocessed, and streamed in real time to ensure system viability in real-world operations. This supplied useful statistics for team evaluation.

Real-World Robustness The operational realism in their design distinguishes these test results. Acubed and SandboxAQ created tests to simulate the “noisy, messy, and unpredictable environments real pilots face every day,” said Elijha Williams, AQNav's technical engagement manager. The highlights of these strong testing were:

A publicly available Beechcraft Baron 58 was used to test AQNav instead of a geosurvey platform. AQNav instrumentation was integrated with minimal aircraft modification, avoiding electromagnetic shielding and noise isolation. AQNav's software kept a clean magnetic signal despite internal interference, and all sensors were strategically located throughout the aircraft. For all flights across the US, Canada, Mexico, and oceans, researchers used the North American Magnetic Anomaly Map (NAMAM). Flight operations included more than 200 continental US airports on a range of operationally critical routes. Importantly, not filtering routes by favourable geomagnetic gradients, map quality, or magnetic anomaly strength tested the system's adaptability. Over 150 flying hours were recorded. Diverse Geophysical Environments: Data was collected from sparsely populated plains to magnetically rich mountainous regions to adequately depict the diverse geographies where aeroplanes operate without GNSS. Genuine Operational Noise Handling: AQNav effectively removed aircraft-generated electromagnetic, vibrational, and other airframe-induced noise. AQNav always outperformed the INS without GNSS in test flights over two hours. AQNav achieved its highest accuracy of less than 74 meters, or two-thirds the length of an American football pitch, during a one-hour flight over tough mountainous and forested terrain in California.

AQNav Sandbox

SandboxAQ, the first dual-use magnetic navigation system, sends real-time positioning data to U.S. iPads. US Air Force aircraft. It has a unique roll-on/roll-off feature that offers live position information during uncontrolled, operational flights.

In 2023, the USAF awarded SandboxAQ a Direct-to-Phase-II Small Business Innovation Research contract to study magnetic anomaly navigation. It completed the AQNav system's initial flight tests eight months early. It contains the largest public Magnetic Navigation database. AQNav has flown 40 missions and 200 hours in four aircraft, from single-engine commercial planes to massive military transports. More flight testing are coming.

In addition to the USAF, Airbus' Silicon Valley R&D centre, Boeing, and other allies are interested in AQNav. The companies are assessing the technology at various phases.

How AQNav Works

AQNav uses sensitive quantum magnetometers to collect data from Earth's crustal magnetic field, which has immutable patterns like human fingerprints and is spatially different.

Comparing this data with magnetic maps utilising unique AI algorithms lets the machine locate itself quickly and accurately. Because quantum sensors are sensitive, AI algorithms boost the signal-to-noise ratio and minimise mechanical, electrical, and other interference that could impair the system's position determination.

Unjammable/Unspoofable Worldwide Signal: Earth's crustal magnetic field is everywhere and provides unfettered access and a dependable signal. AQNav works well as a supplement to other navigation systems because it is weather- and lighting-independent. land Agnostic: AQNav can navigate in the air, over open sea, on distant land, underwater, and underground without visual ground characteristics. Passive Technology: AQNav passively receives geomagnetic data without emitting or reflecting signals to reduce vehicle detection. Flexible, Adaptable Technology: AQNav functions at room temperature without shielding and can be fitted into single-engine and multi-engine airliners. Seamless Integration: AQNav can interface with inertial, visual, satellite, and other cutting-edge navigation systems to create a “system of systems” for safe and precise navigation.

Setting the Stage for GNSS Independence

Due to this big effort, aviation has adopted AQNav more. By maintaining accuracy in an uncontrolled, unfiltered national testbed, SandboxAQ has shown AQNav's viability and operational robustness.

Andrew Sosa Sosanya, SandboxAQ's quantum navigation machine learning engineer, says the “highly relevant MagNav dataset” has a “flywheel effect: the more data it collects, the faster it improves model accuracy across diverse mission profiles,” emphasising its strategic value.

Our advertising showed AQNav's scalability, which is vital to the aviation industry's future, and its impressive performance metrics. Single-flight demos are important proofs of concept, but “scaling is where real progress happens,” the source said. Acubed's Flight Lab's large-scale data collection and analysis accelerated development and validation. This agile platform greatly enhances data collection in actual operating scenarios, accelerating technology maturity and global performance insights.

“AQNav’s recent results have been greatly aided by the relationship with Acubed,” said SandboxAQ staff systems engineer Eddie Rodriguez. It improved navigation accuracy, sped up hardware and software iterations, and characterised aircraft electromagnetic interference noise profiles enabling flight planning improvements and fast feedback loops. Acubed's adaptability in ground tests and EMI surveys “enriched the data pool significantly, pushing the boundaries of sensor placement and denoising capabilities for the next-gen devices,” said SandboxAQ embedded systems engineer Saurabh Kuruvila.