Introduction – Why Inertial Navigation and INS Are Critical
Unmanned systems, whether aerial, underwater, or ground-based, often depend on GNSS and GPS for navigation. These satellite signals, however, are weak and vulnerable. They can be jammed, spoofed, or blocked by terrain, infrastructure, or deliberate electronic warfare. In underwater or subterranean environments, GNSS is unavailable entirely.
INS-DM-FI GPS-Aided INS by Inertial Labs.
This is why inertial navigation systems (INS) have become essential. An INS provides continuous navigation without relying on external signals by combining data from inertial measurement units (IMUs), which house gyroscopes, accelerometers, and sometimes magnetometers. Advanced fiber optic gyroscopes (FOGs) and algorithms for dead reckoning reduce drift and enhance accuracy, making inertial navigation a cornerstone of resilient autonomy.
For UAVs, UUVs, and UGVs operating in GPS-denied environments, INS, IMUs, FOGs, and dead reckoning form the backbone of assured positioning, navigation, and timing (PNT).
What is Inertial Navigation?
Inertial navigation calculates a platform’s position, velocity, and orientation based on its motion over time. An INS takes data from onboard sensors and integrates it to track how far and in what direction the vehicle has moved.
This is achieved through dead reckoning, the continuous estimation of position based on acceleration and angular rate measurements. Unlike GNSS/GPS receivers, inertial navigation requires no external signals. However, the method is prone to drift, as small sensor errors accumulate over time. Managing this drift is the primary challenge of every INS.
IMUs: The Core of Inertial Sensing
At the heart of every inertial navigation system is the inertial measurement unit (IMU). IMUs contain accelerometers and gyroscopes that track movement across three axes. Some also include magnetometers to provide heading references.
MEMS IMUs
MEMS (Micro-Electro-Mechanical Systems) IMUs are the most common type. Lightweight and low-cost, they are found in small drones, smartphones, and robotics. MEMS IMUs are ideal for platforms with strict SWaP (Size, Weight, and Power) requirements. Their drawback is higher noise and drift compared to advanced sensor types.
Tactical-Grade IMUs
Tactical-grade IMUs provide greater accuracy and stability. Used in defense UAVs, UGVs, and UUVs, they allow navigation in GPS-denied environments with minimal drift over extended missions. Tactical-grade IMUs are often coupled with fiber optic gyroscopes or advanced INS algorithms to improve reliability.
Navigation-grade and Strategic-Grade IMUs
FOG Inertial Navigation Systems by GuideNav.
At the high end, navigation-grade IMUs and strategic-grade IMUs offer extremely low drift rates. These are used in submarines, spacecraft, and long-range missiles, where precise inertial navigation over long durations is mission-critical.
FOGs and RLGs in Tactical and Strategic Applications
Fiber Optic Gyroscopes (FOGs)
Fiber optic gyroscopes measure angular velocity using the interference of light traveling in optical fibers. They are extremely accurate, with low drift and high stability.
- Advantages: No moving parts, reliable over long missions, suitable for GPS-denied navigation.
- Applications: Subsea UUV missions, military aircraft navigation, tactical missile guidance.
Ring Laser Gyroscopes (RLGs)
RLGs use laser beams traveling in a closed optical path to detect rotation. Like FOGs, they have no moving parts and offer precise measurements.
- Advantages: Strategic-level accuracy, extremely low drift.
- Applications: Submarines, spacecraft, strategic UAVs.
Both FOGs and RLGs are larger and more expensive than MEMS-based IMUs but are indispensable in high-stakes defense and aerospace operations.
Dead Reckoning and Drift Management
Dead reckoning is the core process of inertial navigation, but its weakness is error growth. Over time, INS drift becomes significant, especially for lower-grade IMUs.
Sources of Drift
-
3DM-CV5-IMU Vertical Inertial Measurement Unit by HBK
Bias: Consistent offset in measurements.
- Noise: Random fluctuations in sensor readings.
- Scale factor errors: Calibration mismatches.
- Environmental effects: Vibration, temperature, and electromagnetic interference.
Drift Reduction Techniques
- Kalman filtering to continuously estimate and correct position errors.
- Sensor fusion with GNSS, Doppler velocity logs (DVLs), or altimeters.
- AI-driven correction models to predict drift patterns and apply real-time adjustments.
For UAVs, UUVs, and UGVs, the combination of INS, IMUs, FOGs, and dead reckoning ensures precise navigation even in highly contested domains.
Integrating INS with Other Navigation Sensors
Modern unmanned systems rarely depend on inertial navigation alone. To achieve assured PNT, multiple sensors are fused together:
- GNSS/INS (INS + GNSS hybrids): GNSS corrects INS drift when available, while the INS ensures continuity in denied conditions.
- Doppler Velocity Logs (DVLs): Common in UUVs, providing drift correction by measuring velocity relative to the seabed.
- Altimeters and odometers: Ground vehicles combine IMUs with wheel encoders and barometric sensors.
- Vision-based navigation (SLAM): UAVs and UGVs increasingly use lidar, radar, and cameras for drift correction.
This layered architecture creates navigation systems that remain resilient under GNSS denial.
Applications of Inertial Navigation in Unmanned Systems
UAVs – BVLOS Operations and Contested Airspace
Unmanned Aerial Vehicles (UAVs) rely on IMUs and INS to maintain flight stability and course when GNSS is unavailable. For Beyond Visual Line of Sight (BVLOS) operations, INS provides critical resilience.
Case Study: Military UAVs on ISR missions in contested airspace use tactical-grade IMUs and FOGs to ensure reliable navigation despite jamming and spoofing.
UUVs – Subsea Survey and Mine Countermeasures
Unmanned Underwater Vehicles (UUVs) operate in GPS-denied environments by default. Their navigation relies almost entirely on inertial navigation systems, often paired with DVLs for drift correction.
Case Study: UUVs used in pipeline inspections employ INS + DVL to track precise positions across survey grids, ensuring mission accuracy even after hours underwater.
UGVs – Subterranean and Tactical Logistics
Unmanned Ground Vehicles (UGVs) use INS and IMUs to navigate tunnels, forests, and urban canyons. Sensor fusion with odometers and SLAM enhances accuracy.
Case Study: UGV convoys equipped with dead reckoning INS and tactical-grade IMUs continue operations under electronic warfare conditions, ensuring logistics chains remain intact.
Benefits of Inertial Navigation in GNSS-Denied Environments
- Resilient autonomy: INS and IMUs enable continuous navigation when GNSS is blocked.
- Mission assurance: UAVs, UUVs, and UGVs can complete tasks reliably.
- Safety: Prevents vehicle loss and navigational errors.
- Defense compliance: Meets assured Positioning, Navigation, and Timing (PNT) requirements.
Future of Inertial Navigation for Autonomous Systems
The future of inertial navigation and INS lies in combining smaller, smarter sensors with advanced correction methods:
- Miniaturized MEMS IMUs are expanding their use in smaller drones and robotic platforms.
- AI-driven drift correction enhances dead reckoning performance.
- Next-gen gyroscopes (FOGs, RLGs, quantum sensors) are being developed for defense-grade applications.
- Multi-sensor fusion with vision, lidar, and radar will define resilient autonomy.
For unmanned systems, this means that INS, IMUs, FOGs, and dead reckoning will remain foundational technologies, ensuring autonomy where GNSS cannot be trusted.
In an era where GNSS denial is a growing risk, unmanned platforms cannot depend solely on satellites. Inertial navigation systems (INS), powered by high-grade IMUs, stabilized by FOGs, and corrected with advanced dead reckoning, provide the resilient backbone for UAVs, UUVs, and UGVs.
As miniaturization, AI, and sensor fusion continue to advance, inertial navigation will remain the bedrock of assured autonomy in defense, aerospace, and commercial operations.
When GNSS is contested or unavailable, inertial navigation delivers the autonomy that unmanned systems need.
