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.

The DiSTFA method (Displacements and Strains using Transformation and Free Adjustment) was presented in Kamiński (2009). The method has been developed for the determination of displacements and strains of engineering objects in unstable reference systems, as well as for examining the stability of reference points. The DiSTFAG (Gross errors) method presented in the paper is the extension of the DiSTFA method making it robust to gross errors. Theoretical considerations have been supplemented with an example of a practical application on a simulated 3D surveying network.

The paper presents the results of research on the possibilities of fixing ship position coordinates based on results of surveying bearings on navigational marks with the use of the CCD camera. Accuracy of the determination of ship position coordinates, expressed in terms of the mean error, was assumed to be the basic criterion of this estimation. The first part of the paper describes the method of the determination of the resolution and the mean error of the angle measurement, taken with a camera, and also the method of the determination of the mean error of position coordinates when two or more bearings were measured. There have been defined three software applications assigned for the development of navigational sea charts with accuracy areas mapped on. The second part contains the results of studying accuracy in fixing ship position coordinates, carried out in the Gulf of Gdansk, with the use of bearings taken obtained with the Rolleiflex and Sony cameras. The results are presented in a form of diagrams of the mean error of angle measurement, also in the form of navigational charts with accuracy fields mapped on. In the final part, basing on results obtained, the applicability of CCD cameras in automation of coastal navigation performance process is discussed.

The work presents the results of studies on dependence of effectiveness of chosen robust estimation methods from the internal reliability level of a geodetic network. The studies use computer-simulated observation systems, so it was possible to analyse many variants differing from each other in a planned way. Four methods of robust estimation have been chosen for the studies, differing substantially in the approach to weight modifications. For comparative reasons, the effectiveness studies have also been conducted for the very popular method in surveying practice, of gross error detection basing on LS estimation results, the so called iterative data snooping. The studies show that there is a relation between the level of network internal reliability and the effectiveness of robust estimation methods. In most cases, in which the observation contaminated by a gross error was characterized by a low index of internal reliability, the robust estimation led to results being essentially far from expectations.