Comparative Analysis of Fusion Algorithms in a Loosely-Coupled Integrated Navigation System on the Basis of Real Data Processing

The paper presents a comparative analysis of the extended Kalman filter (EKF) and the sigma-point Kalman filter (SPKF) applied to solve the problem of SINS/GNSS integration based on a loosely-coupled integration scheme. Complete stochastic measurement models of MEMS inertial sensors are considered. The efficiency of the EKF and the SPKF is evaluated using real experimental data on complex motion from an SINS based on MEMS technology and a GNSS receiver with a double antenna. The estimation accuracy of navigation parameters using the EKF and the SPKF in the presence of the GNSS signal and during the GNSS outages is analyzed. The results of the statistical analysis of the errors in estimating navigation parameters for different periods of GNSS signal outage are considered.

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