Strapdown Inertial Navigation with IMU
Knowing the technology that makes it possible to navigate accurately without the help of external references.
An Inertial Measurement Unit (IMU) is an electronic device which measures the value of a body’s specific force and angular rate, and sometimes orientation about the body, through a combination of accelerometers, gyroscopes, and sometimes magneto-meters. When combined with navigation algorithms it forms an Inertial Navigation System (INS).
What is Strapdown Inertial Navigation?
Strapdown Inertial Navigation is more a modern approach, in which the inertial sensors are mounted directly to the vehicle or device (“strapped down” to it), rather than being mounted on a stabilized platform. The system is based on complex algorithms that calculate the position, the velocity and the orientation using the raw data from the sensors.
Essential Elements of IMU Based System for Navigation
Accelerometers
Measure linear acceleration both in 3 perpendicular (X, Y, Z) directions If we integrate the acceleration once we will have the velocity, finally integrate any acceleration with time we will get the position.
Gyroscopes
Measuring angular velocity or rotation of the object or body around three axes. This information is important for measuring the changes in orientation over time.
Magnetometers
Optional sensors for measuring the Earth’s magnetic field for points of an absolute heading reference and gyroscope drift compensation.
Processing Unit
Runs navigation algorithms that process the raw data from the sensors and translate this into usable data about the position, velocity and orientation.
How Strapdown INS Works
The basic principle behind this is dead reckoning, i.e. starting from a known position, the system constantly integrates the measurements of acceleration and rotation in order to update the position and the rotation.
1. Initialization
The system requires three initial parameters, position, velocity, and orientation. This can be supplied by GPS, manual input or other reference systems.
2. Sensor Measurement
Accelerometers read the measure of specific force (including gravity), gyroscope – angular rates. These measurements are done at high frequency (usually 100-1000Hz).
3. Attitude Update
The gyroscope data is used to update into the orientation (roll, pitch, yaw) of the system. This is usually achieved by the use of quaternions or rotation matrices.
4. Coordinate Transformation
Accelerometer measurements are converted from body frame when converted to navigation frame, based on what the current orientation is.
5. Gravity Compensation
Gravity is subtracted from the transformed accelerations in order to get the true kinematic acceleration.
6. Integration
Acceleration is integrated once to get velocity, one more time to get position. This process keeps continuing recursively.
Key Applications
Aerospace & Aviation
Used in aircraft to provide attitude and heading reference systems (AHRS), flight control and as back-up in the event that GPS function is not available.
Autonomous Vehicles
Offers continuous positioning between GPS updates and handling concerned locations such as tunnels or an urban canyon where GPS is denied.
Robotics & Drones
Enables the ability to stabilize, navigate and control unmanned systems with no external references.
Marine Navigation
Used for ships and submarines to have accurately navigated especially when submerged where GPS is unavailable.
Virtual Reality
Tracks head and controller movements with high-frequency, low-latency so that it can be used to create immersive experiences.
Personal Navigation
Implemented in Smartphones and wearables such as for step counting, activity recognition and indoor navigation.
Advantages and Challenges
| Advantages | Challenges |
|---|---|
| Self-contained (no external signals will be required) | There is a drift in position error as a result of time. |
| High update rate (100-1000Hz) | Sensitive to the Sensor biases and noise |
| Works in GPS denied environment | Initial alignment required |
| Guarantees full motion data (location, speed, attitude) | Temperature sensitivity has an impact to accuracy. |
| Not affected by weather conditions | Complex processing Algorithms |
Technology Evolution
1960s-1970s
Platform Systems
Gimballed platforms for physical stabilization of the sensors were used very early in INS. These systems were massive and costly and mechanically complicated.
1980s-1990s
Early Strapdown Systems
Total conversion to fixed calculating sensors. Smaller size and cheaper price but used more processing power.
2000s-2010s
MEMS Revolution
Micro-Electro-Mechanical Systems (MEMS) had the ability to make IMUs smaller, less costly, and increase their reliability, which opened up the consumer market.
Present & Future
Sensor Fusion & AI
IMU combined with GPS, cameras and lidar are advanced algorithms. Machine learning leads to better modeling of errors and compensations.
Conclusion
Strapdown inertial navigation using IMUs is basic technology to modern navigation systems. While there is a buildup of a significant drift in standalone IMUs over time, when operated in combination with other sensors and elaborate algorithms, they deliver robust, continuous and high precision navigation solutions in countless applications. As IMU technology continues to improve in terms of accuracy and affordability while decreasing in size and power consumption, we can expect to see even wider adoption in the areas of autonomous systems, consumer electronics and new technologies.