Integrated Systems for Land Vehicle Navigation

Abstract

Low-cost, Micro Electrical Mechanical Systems (MEMS) based inertial sensors have gained an increasing interest with the growing dependence on unmanned systems and small guided aerial vehicles. Building an Inertial Navigation Systems (INS) based on this technology is a challenging task due to the associated degraded accuracy and noisy measurements. That led a lot of researchers to work in this interesting area and to focus in the issue of enhancing the localization and navigation performance. MEMS based navigation systems are used in unmanned aerial vehicles (UAVs), guided, autonomous and land vehicles because of their low weight, low size and low power consumption compared with the previous systems which are heavy and are characterized by their high cost, high consumption of energy. The requirements of any used INS are to provide high rate and accuracy information about the position, velocity and attitude over a certain period of time. Some problems related to MEMS usage is the deviation of the accuracy of the readings over time. Global Positioning System (GPS) provides more accurate and continuous position and velocity calculations, but with a lower measurements rate. Furthermore, satellite signals are not always available in different conditions such as urban canyons, tunnels, and even indoor situations such as parking lots. GPS/INS integration based on Kalman filter (KF) has proven to be a reliable solution to overcome on the drawbacks of both of them.