Research Of Low-cost Integrated Navigation System

The integrated navigation system of Strapdown Inertial Navigation System and Global Positioning System is an ideal integrated mode, which has advantages of low cost, high precision, and good reliability, since it has integrated the advantage of good reliability of SINS and high precision of GPS. GPS/SINS integrated navigation system has two integrated mode in this thesis, one is No Gyro Integrated Navigation System, the other is Integrated Navigation System with Gyroscope. The attitude angles of the No Gyro Integrated Navigation System are calculated by accelerometer and reluctance. Integrated Navigation System with Gyroscope improves the system dynamic performance by introducing a gyroscope on the basis of the No Gyro Integrated Navigation System. This thesis studied the filtering method of the integrated navigation systems in depth and established the simulation systems to test the filtering effect.Firstly, the thesis introduced present situation of the navigation system, then the basic principle of SINS and GPS was introduced. The error model of SINS and GPS was established, and the application of kalman filter in GPS/SINS integrated navigation system had be described.Secondly, the thesis focused on the principle and characteristics of the two kinds of integrated navigation systems, and different status equations and measurement equations was established according to different characteristics of various kalman filters.Finally, the GPS/SINS semi-physical simulation integrated navigation system was established. The carrier locus had be simulated by mathematical method, the output results of gyroscope,accelerometer and reluctance were simulated, then the results were integrated with simulation GPS data in order to establish integrated navigation system. Standard Kalman Filter, Improved Adaptive Filter were designed. Experiment results shows that Improved Adaptive Filter is more precise than standard Kalman Filter, it can improve the precision of the system and make the system more optimal.