Quantum Navigation
Resilient Positioning Without GPS
Quantum navigation is becoming one of the most practical answers to a growing problem: GPS is not always available, and it is not always trustworthy. When GPS is denied, degraded, spoofed, or jammed, systems still need to know where they are and where they are going. That is the promise of quantum navigation — resilient positioning that does not depend on receiving an external signal.
SandboxAQ's AQNav is built for this exact use case, combining advanced sensing with AI-driven inference for operations in GPS-challenged environments.
Why quantum navigation is showing up now
For years, GPS was treated as a given. Today, many operators plan under the assumption that GPS can be disrupted.
The reasons are straightforward:
- Interference is easier to create than most people realize
- Spoofing can mislead systems, not just deny them
- Many environments have signal limitations that make GPS unreliable
- Critical operations cannot afford navigation failure
Quantum navigation fits here because it is designed to continue operating when GPS cannot be trusted.
What quantum navigation is, in plain terms
Quantum navigation uses high-precision sensors that can measure motion and environmental signals with exceptional sensitivity. Paired with modern computation, those measurements can be used to estimate position and trajectory even when satellite signals are unavailable.
A practical way to think about it:
- GPS relies on external signals from satellites
- Quantum navigation relies on internal sensing and inference
That shift is why it is often discussed alongside "assured navigation" or "resilient PNT" concepts.
How quantum navigation relates to magnetic navigation
In real-world systems, quantum navigation is often paired with ideas from magnetic navigation, where Earth's magnetic field becomes an input signal for positioning. This is sometimes referenced as MagNav-style navigation for aviation and other demanding use cases.
Magnetic navigation is attractive because it can be:
- passive (no transmissions)
- resilient in contested environments
- useful as a complementary signal when other sources degrade
In practice, these approaches often converge into a broader sensor fusion story, where multiple independent signals support robust positioning.
Where the AI matters
Sensors do not solve navigation alone. They produce streams of data, and the system must convert those streams into reliable position estimates.
AI supports:
- filtering and denoising
- map matching
- anomaly detection
- sensor fusion across multiple inputs
- real-time estimation under uncertainty
SandboxAQ's work on Large Quantitative Models is directly relevant here — quantitative modeling is what makes inference reliable in complex physical systems like these.
What quantum navigation solves that GPS cannot
GPS denial
In some environments, GPS signals may be unavailable or blocked. Quantum navigation is designed to continue operating without external signals.
GPS jamming
Jamming can overwhelm receivers, causing loss of signal. Resilient navigation needs alternatives that remain viable under interference.
GPS spoofing
Spoofing is more dangerous than jamming because the system may still "think" it has GPS while the position is wrong. A resilient approach needs independent signal sources to detect and reduce the impact of spoofing.
Who needs quantum navigation
Quantum navigation is most relevant when:
- downtime or misnavigation has high consequence
- operations occur in environments where interference is likely
- systems must remain reliable without reliance on external transmissions
That includes defense-adjacent contexts, aviation, and other critical operations where assured navigation is a requirement, not a nice-to-have.
What to evaluate in a quantum navigation solution
If you are looking at solutions, focus on these practical factors.
Resilience
- How does it perform when GPS is degraded or denied?
- What independent signals does it use to stay accurate?
Integration
- How does it integrate with existing systems and workflows?
- Is it designed for operational environments, not just labs?
Operational monitoring
- Can it detect anomalies consistent with spoofing or drift?
- Does it provide confidence estimates and alerts?
Performance and practicality
- Can it operate in real-time?
- What are the constraints for deployment, calibration, and maintenance?
AQNav is SandboxAQ's solution for teams operating in GPS-challenged environments.
To explore resilient navigation approaches from SandboxAQ: