Pedestrian Inertial Navigation with Self-Contained Aiding. Andrei M. Shkel
Aiding Techniques Based on Natural Signals
Magnetometry and barometry are two commonly applied techniques that are used to improve the navigation accuracy. Magnetometry is one of the most ancient aiding techniques developed for navigation applications, where measurement of the Earth's magnetic field can provide information about the orientation of the system. Nowadays, not just the orientation, but also the location of the system can be obtained by measuring the anomalies of the Earth's magnetic field in the navigation of low‐earth‐orbiting spacecraft (altitude less than 1000 km), where the position of the spacecraft can be estimated with resolution on the order of 1 km. Barometry estimates the altitude of the system by measuring the atmospheric air pressure. It has been shown that low altitudes above sea level, the atmospheric pressure decreases approximately linearly as the altitude increases with a rate of about 12 Pa/m. A pressure measurement resolution of 1 Pa, or an altitude measurement accuracy of less than 0.1 m, can be achieved with the currently available commercial micro barometers [26].
Another way of implementing estimations of absolute position is through computer vision, where images of the environment are captured to extract information. One of the most popular implementations is called the Simultaneous Localization and Mapping (SLAM), where the localization and mapping of the environment is conducted simultaneously. As a result, no pre‐acquired database of the environment is needed. The sensors used for this application do not necessarily have to be cameras, LIght Detection And Ranging (LIDAR) and ultrasonic ranging can also be used. In either case, the system extracts some information about the environment as an aiding technique to improve the navigation accuracy.
1.4.1.2 Aiding Techniques Based on Artificial Signals
Radio‐based navigation is another popular technique in this category. It was first developed in the early twentieth century and its application was widely developed in the World War II. More recently, it was considered as a reliable backup of the global positioning system (GPS) in the United States, and could reach a navigation accuracy of better than 50 m. One of the most common aiding techniques in this category is Global Navigation Satellite System (GNSS), where a satellite constellation is implemented in the space as “landmarks,” transmitting radio waves for navigation purposes. The navigation accuracy of GNSS for civilian use is currently about 5 m along the horizontal direction, and about 7.5 m along the vertical direction. Long‐term evolution (LTE) signals have also been proposed and demonstrated to be used for navigation purposes. The principle of LTE‐based navigation is similar to GNSS, except that the landmarks are the LTE signal towers instead of satellites. The greatest advantage of LTE over GNSS is its low cost, since no special signal towers has to be established and maintained. Currently, a horizontal navigation accuracy of better than 10 m has been reported.
In the case of short‐range navigation aiding techniques, Ultra‐Wide Band (UWB) radio, WiFi, Bluetooth, and Radio‐Frequency Identification (RFID) have all been explored. They are typically used in indoor navigation due to their short signal propagation range. Unlike radio‐based navigation, in which the radio frequency is fixed, UWB radio occupies a large bandwidth (
Table 1.1 Summary of non‐self‐contained aiding techniques.
| Aiding technique | Applicable area | Positioning accuracy (m) | Notes |
|---|---|---|---|
| GPS | Above earth surface | 5 | Large signal coverage area Unavailable below the Earth's surface and in complex urban areas Susceptible to jamming and spoofing |
| LTE/5G | Mostly in urban areas | 10 | No extra infrastructure needed Rely on cellular signal coverage |
| Radar | In the air | 50 | Cheap and robust to different weathers Very large effective range Signal can penetrate insulators but will be obstructed by conductive material |
| UWB | Mostly indoor | 0.01 | Very accurate distance measurement in a short range Simple hardware with low power consumption Susceptible to interference |
| Lidar | In the air | 0.1 | Accurate position and velocity measurement Affected by the weather, such as strong sunlight, cloud, and rain |
| WiFi | Indoor | 1 | A priori knowledge of WiFi router is needed Algorithm is needed to compensate for signal strength fluctuations |
| Bluetooth | Indoor | 0.5 | Moderate measurement accuracy with very low power hardware Short range of measurement (<10 m) |
| RFID | Indoor | 2 | Easy deployment Very short range of measurement |
1.4.2 Self‐contained Aiding Techniques
Another category of aiding techniques is self‐contained aiding. Instead of fusing external signals into the system, self‐contained aiding takes advantage of the system's patterns of motion to compensate for navigation errors. Therefore, self‐contained aiding techniques vary for different navigation applications due to different dynamics of motions.
For example, in ground vehicle navigation, the wheels can be assumed to be rolling without slipping. Thus, IMU can be mounted on the wheel of the vehicle to take advantage of the rotational motion of the wheel. In this architecture, the velocity of the vehicle can be measured by multiplying the rotation rate of the wheel by the circumference of the tire [28]. In addition, carouseling motion of the IMU provides the system more observability of the IMU errors, especially the error of yaw gyroscope, which is typically nonobservable in most navigation scenarios [29]. Besides, low frequency noise and drift can also be reduced by algorithms taking advantage of the motion of the IMU [30].
Another approach is to take advantage of biomechanical model of human gait instead of just the motion of the foot during walking. This approach typically requires multiple IMUs fixed on different parts of human body and relate the recorded motions of different parts through some known relationships derived from the biomechanical model. In this approach,