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Abstrakt

The paper expounds relevant results of some of the present author’s experi- ments defining the strapdown IMU sensors’ errors and their propagation into and within DGPS/IMU. In order to deal with this problem, the author conducted both the laboratory and field-based experiments. In the landborne laboratory the stand-alone Low-Cost IMU MotionPak MKII was verified in terms of the accelerometer bias, scale factor, gyroscope rotation parameters and internal temperature cross-correlations. The waterborne field-trials based on board dedicated research ships at the lake and at the busy small sea harbour were augmented by the landborne ones. These experiments conducted during the small, average, and high dynamics of movement provided comparative sole- GPS, stand-alone DGPS and integrated DGPS/IMU solution error analysis in terms of the accuracy and the smoothness of the solution. This error estimation was also carried on in the context of the purposely-erroneous incipient DGPS/IMU initialisation and alignment and further in the circumstances of on-flight alignment improvement in the absence of the signal outages. Moreover, the lake-waterborne tests conducted during extremely low dynamics of movement informed about the deterioration of the correctly initialised DGPS/IMU solution with reference to the stand-alone DGPS solution and sole- GPS solution. The above-mentioned field experiments have checked positively the DGPS /MKI research integrating software prepared during the Polish/German European Union Research Project and modified during the subsequent Project supported by the Polish Committee for Scientific Research.
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Abstrakt

The BeiDou navigation satellite system (BDS) is one of the four global navigation satellite systems. More attention has been paid to the positioning algorithm of the BDS. Based on the study on the Kalman filter (KF) algorithm, this paper proposed a novel algorithm for the BDS, named as the minimum dispersion coefficient criteria Kalman filter (MDCCKF) positioning algorithm. The MDCCKF algorithm adopts minimum dispersion coefficient criteria (MDCC) to remove the influence of noise with an alpha-stable distribution (ASD) model which can describe non-Gaussian noise effectively, especially for the pulse noise in positioning. By minimizing the dispersion coefficient of the positioning error, the MDCCKF assures positioning accuracy under both Gaussian and non-Gaussian environment. Compared with the original KF algorithm, it is shown that the MDCCKF algorithm has higher positioning accuracy and robustness. The MDCCKF algorithm provides insightful results for potential future research.
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