An Integrated Navigation System of NGIMU/ GPS Using a Fuzzy Logic Adaptive Kalman Filter

Abstract

AbstractThe Non-gyro inertial measurement unit (NGIMU) uses only accelerometers replacing gyroscopes to compute the motion of a moving body. In a NGIMU system, an inevitable accumulation error of navigation parameters is produced due to the existence of the dynamic noise of the accelerometer output. When designing an integrated navigation system, which is based on a proposed nine-configuration NGIMU and a single antenna Global Positioning System (GPS) by using the conventional Kalman filter (CKF), the filtering results are divergent because of the complicity of the system measurement noise. So a fuzzy logic adaptive Kalman filter (FLAKF) is applied in the design of NGIMU/GPS. The FLAKF optimizes the CKF by detecting the bias in the measurement and prevents the divergence of the CKF. A simulation case for estimating the position and the velocity is investigated by this approach. Results verify the feasibility of the FLAKF.KeywordsGlobal Position SystemResidual ErrorInertial FrameInertial Measurement UnitAngular RateThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.