Kalman Filter And Improve Algorithm In INS/GPS Integrated Navigation System

Inertial Navigation System (INS) is a completely independent navigation system,which can provide all-weather and hidden navigation information. The INS is alsowith its fatal short point, such as its running accuracy is high only within a short time,the location error of INS can be accumulated over time and long time positioningaccuracy will come to worse. When Global Position System (GPS) proceed long-termpositioning, the positioning error is small, but its location will be effect on otherelectromagnetic wave and signal shielding problems, short time positioning is bad.Combination INS and GPS to form INS/GPS integrated navigation system,it canlearn from each other and it is a relatively ideal navigation system.This paper introduces working principle and components of INS, Introducescoordinates systems and transformations. And then introduces the structure, workingprinciple of GPS system, analyzes the errors in GPS in detail.This paper establishes the error model of INS/GPS integrated navigation system,gives error equations of INS and GPS, gives the state equation and measurementequation, then discretizate them.Introduced conventional Kalman filter in detail, infer the filtering equations,based on Kalman filtering algorithm analysis of the Sage-Husa adaptive filteringalgorithm, introduces an improved Sage-Husa adaptive filtering algorithm and givesthe filtering equation.Finally, apply improve Sage-Husa adaptive filtering algorithm in INS/GPSintegrated navigation system and the simulation in MATLAB. The simulation resultsshow that filtering effect of improved Sage-Husa adaptive filtering algorithm issuperior to Kalman filtering algorithm, especially longitude location error and latitudelocation error, the improved Sage-Husa adaptive filtering algorithm to ensure thestability of INS/GPS system and improve the system accuracy.