Abstract
Chapters 8 is intended to provide an introduction to the use of inertial sensors as part of a solution for GPS denied navigation system. An inertial navigation systems (INS) is a navigation system that provides position, orientation, and velocity estimates based solely on measurements from inertial sensors. Inertial measurements are differential measurements in the sense that they quantify changes in speed or direction. The two primary types of inertial sensors are accelerometers and gyroscopes. These sensors discussed have complementary error characteristics to RF sensors and so can enable mitigation of the effects of multipath and NLOS errors in the location solution. A main drawback of using purely inertial systems for navigation is that errors in the differential measurements are necessarily accumulated in the navigation solution over time. Thus, even with highly precise inertial measurements, position estimates based on them degrade over time. The key to making inertial sensors part of a precision positioning system is developing methods to both minimize free inertial position error growth and bound accumulated inertial position errors. It is now well accepted that a high accuracy navigation solution requires the ability to fuse input from multiple sensors making use of all available navigation information. In Chapter 8 we discuss fusion of inertial sensor data with sensors and/or algorithms that provide estimates of secondary inertial state variables such as velocity, heading, and elevation.
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Notes
- 1.
The ground truth location is obtained by pinning the drift compensated inertial path at each of several surveyed marker locations to the surveyed marker location, and then interpolating the inertial tracks between the surveyed marker points. Inherent in this method is an assumption that the approximate inertial path shape (after compensation for drift and scaling errors) for the collected data is correct.
- 2.
The CEP or circle of equal probability is the radius of a circle whose boundary contains 50Â % of the errors. While 50Â % is a very common definition for CEP, the circle dimension can be defined for different percentages.
- 3.
Bosch BMP180 MEMS Pressure Sensor.
- 4.
The iPhone 4 also includes STMicroelectronics’ LIS331DLH MEMS accelerometer as well as its L3G4200D MEMS digital three-axis gyroscope.
- 5.
Run-to-run bias is higher and the assumption is that constant offset can be compensated by filtering methods (Kalman filter or other) but the variation around that bias (in-run bias stability) is harder to compensate.
- 6.
If the pitch and roll are not known precisely they can be estimated using the accelerometer data directly or by using an extended Kalman filter which takes advantage of the fact that the tilt errors will be correlated with horizontal velocity errors.
- 7.
Short is relative to the quality of the gyroscope. Refer to Table 8.1 for typical gyro drift rates by class.
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Gentile, C., Alsindi, N., Raulefs, R., Teolis, C. (2013). Inertial Systems. In: Geolocation Techniques. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1836-8_8
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