In the vast deep sea, the boundless sky and the complex underground cities, when satellite signals are blocked or even completely fail, how can we determine precise position, speed and attitude information? The answer is “inertial navigation” – a completely autonomous navigation technology that does not rely on external signals. The core of the inertial navigation system lies in its internal inertial sensors (gyroscopes and accelerometers). They continuously monitor the movement changes of the carrier, and through precise integration and calculation of these raw data, Inertial navigation can independently and continuously calculate the three-dimensional position, velocity and attitude angle of the carrier. With the rapid development of technology, inertial navigation systems have evolved into various architectures. The core classification dimension lies in the physical layout of the inertial measurement unit (IMU) and the data processing mechanism. At present, inertial navigation is mainly divided into platform-based inertial navigation and strapdown inertial navigation. A thorough understanding of the different categories of inertial navigation is crucial for grasping the application boundaries and performance characteristics of this technology. These classifications laid the foundation for the development of modern autonomous navigation systems.
Depending on the established coordinate system, the platform-type inertial navigation system operates in two modes: spatial stabilization and local horizontal positioning. The platform of the space-stabilized platform-type inertial navigation system remains stable in the inertial space. It is used to establish the inertial coordinate system, and the effects of the Earth’s rotation and gravitational acceleration are compensated by the computer. This kind of inertial navigation system is mostly used in the active parts of launch vehicles and some spacecraft. The characteristic of the local horizontal platform inertial navigation system is that the reference plane formed by the two acceleration sensor input axes on the platform can always track the horizontal plane of the point where the aircraft is located (by using acceleration sensors and gyroscopes to form a Schuler loop), so the acceleration sensor is not affected by the gravitational acceleration. This inertial navigation system is mostly used in aircraft (such as airplanes) that move at a constant speed along the Earth’s surface. In platform-based inertial navigation, the frame can isolate the angular vibrations of the aircraft, and the instrument working conditions are better. This platform can directly establish the navigation coordinate system, with a small amount of calculation and easy compensation and correction of instrument outputs. However, the structure is complex and the volume is large.
Depending on the type of gyroscope used, strapdown inertial navigation can be further classified into rate-type strapdown inertial navigation systems and position-type strapdown inertial navigation. The rate-type strapdown inertial navigation system uses the instantaneous average angular velocity vector signal output by the rate gyroscope; Position-based strapdown inertial navigation uses the angular displacement signals output by the free gyroscopes. The strapdown inertial navigation system does not require a platform, has a simple structure, is small in size, and is easy to maintain. However, when gyroscopes and accelerometers are directly installed on the aircraft, the working conditions are poor, which will reduce the accuracy of the instruments. The output of the system accelerometer is the acceleration components in the vehicle body coordinate system. These need to be converted into the acceleration components in the navigation coordinate system by a computer, which involves a large amount of calculation.
To obtain the precise position data of the aircraft, it is usually necessary to conduct a comprehensive calculation of the output from each measurement channel of the inertial navigation system. However, the inherent errors of inertial navigation accumulate over time: the constant drift of the gyroscope causes the angular measurement error to increase linearly over time, while the constant bias of the accelerometer leads to position errors that are proportional to the square of time, Such errors have a divergent nature and will continue to increase. To suppress this divergence and improve accuracy, we can correct it by constructing three key negative feedback loops: the Shura loop (eliminating the influence of accelerometer bias on the horizontal position), the Gyro Compass loop (using the gravitational effect to precisely find the north direction), and the Foucault loop (suppressing the characteristic damping of the Shura loop’s periodic oscillation, with a period of approximately 24 hours).
It is worth noting that the Shura loop, the Gyro Compass loop and the Foucault loop all exhibit the characteristic of undamped periodic oscillation.Therefore, in practical applications, inertial navigation systems are often combined with external navigation systems such as radio navigation, Doppler navigation, and celestial navigation to form a combined navigation system.This approach not only introduces damping but also provides external correction information, thereby achieving more accurate navigation output.
Furthermore, the navigation accuracy of the inertial navigation system is highly dependent on the accuracy of geophysical parameters (such as the shape and gravitational field of the Earth). High-precision inertial navigation systems require the calculation of Earth parameters based on the reference ellipsoid model. However, due to factors such as uneven crustal density and topographic fluctuations, the actual gravitational acceleration values at different points on the Earth’s surface usually differ from the theoretical calculated values of the reference ellipsoid model. This difference is random and is known as gravitational anomaly. The currently developing gravity gradient instrument technology can measure the local gravity field gradient information in real time, providing more accurate geophysical parameters, and thus is expected to solve the problem of interference caused by gravity anomalies on high-precision inertial navigation.
