
Inertial navigation systems are in common use for decades due to its advantages. Since INS outputs are usually used for inputs in different control algorithms (depending on applications), INS will induce certain errors and limitations. This chapter deals with optimization of the inertial navigation algorithm against limitations due to the accuracy and stability of signals from the sensors and constraints resulting from the integration step and processor speed used for embedded applications. Inertial navigation considered here is “strapdown” inertial navigation system (SINS) which assumes a fixed inertial measurement unit (IMU). In this chapter, fundamentals of strapdown inertial navigation will be presented as well as three different algorithms which will be analyzed in regard to numerical stability, time consumption and processor load criteria.
quaternions, forward Euler integration, code analyses, strapdown inertial navigation system, code optimization
quaternions, forward Euler integration, code analyses, strapdown inertial navigation system, code optimization
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
