It is well known that RTK (Real Time Kinematic) positioning is a very efficient technique for determination of coordinates in real time, directly on location. Although this technique has been well known since the mid-nineties of the last century, the common use of this technique developed since permanent reference GNSS (Global Navigation Satellite Systems) stations started operating as the national reference systems. Positioning in real time is very convenient for users who do not need to know any advanced technique of post-processing, especially in cases when no obstructions exist around the measured point exist. However, in practice, there are some situations when the use of RTK technique makes some difficulties, especially if the GNSS receiver has no full availability of satellites. Obstructions caused by trees, buildings, power lines etc. limit satellite availability and in consequence decrease the reliability of determined coordinates significantly. In those situations gross errors of even meters can appear in RTK positioning. In order to avoid misleading coordinates occurring we can use more than one RTK receiver simultaneously. The paper presents an approach to the RTK technology based on the simultaneous use of three different RTK receivers. Three different GNSS/RTK receivers can be set on a special mounting beam and additionally RTK positions are sent in real time to a computer. The computer software analyses not only the precision but also checks the accuracy and reliability of the RTK positions determined. Consequently, the new approach to RTK survey presented can allow obtaining reliable coordinates of centimeter accuracy even under very severe forest conditions.
The presence of terrain obstacles, for instance in urban, mountain or forest environments, significantly affects the accuracy of global navigation satellite system (GNSS) measurements, due to signal reception blockage and the multipath effect. The multipath remains a domain source of ranging errors in satellite positioning. When considering a session of a few hours, this type of error cannot be eliminated by differential techniques because its influence is uncorrelated with time and space. In order to minimize the influence of multipath, various methods can be applied. We present a data preprocessing tool for GPS multipath detection and mitigation based on GNSS obstacle mapping. Because reception of non-line-of-sight signals is closely connected with the place of observation, the maps of obstacles derived from on-point hemispherical images were applied. The main assumption of the proposed method is to remove from observations those received from satellites, which according to the map were behind the obstacle. As a reference two data sets were used. The first one was a set of unfiltered observations. In the second data set used for comparison there were measurements for which the C/N0 value was greater than 40 dB Hz−1. The research showed that if the data registered from obstructed signals is deleted, the positioning accuracy will be better, despite the decreasing visible satellites number and the dilution of precision coefficient devaluation.
Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.
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