Abstract:
Nowadays, the integration of INS with GPS leads to many applications, mainly driven by
the development of low-cost MEMS sensors. Then, it is not surprising that great interest has been
generated toward low cost inertial sensors in the last decade. Although the basic principles of INS are
quite simple, the analysis of its performance and the impact of sensor quality on the overall result are
quite complex. In fact, one particular aspect of INS design is the complexity to evaluate new
algorithms and innovative digital signal processing with various sensors and to access their
performances in function of several kinds of mobile trajectories. Therefore, as most engineering
applications, the simulation can be considered an important step to implement INS/GPS integration
algorithms. Therefore, this paper exploits a simulation platform for INS/GPS integrated systems. It
consists of a trajectory generator, GPS simulator; IMU simulator, and optimal estimation engine.
Kalman filter algorithm plays a major role in the proposed platform. It is utilized in loosely coupled
architecture as the core of optimal estimation engine, inertial sensor error models, and INS
mechanizations. It also provides the facility to give a real time test. The proposed platform can be
regarded as a cost-effect tool to study the techniques concerning INS/GPS integrated system. It can be
used for research as well as education purposes. Several practical issues concerning the
implementation of INS/GPS integration algorithms are discussed to demonstrate the capability of
proposed platform.