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This paper aims to present the problem of the integration of the global positioning system (GPS)/global navigation satellite system (GLONASS) data for the processing of aircraft position determination.

The aircraft coordinates were obtained based on GPS and GLONASS code observations for the single point positioning (SPP) method. The numerical computations were executed in the aircraft positioning software (APS) package. The mathematical scheme of equation observation of the SPP method was solved using least square estimation in stochastic processing. In the research experiment, the raw global navigation satellite system data from the Topcon HiperPro onboard receiver were applied.

In the paper, the mean errors of an aircraft position from APS were under 3 m. In addition, the accuracy of aircraft positioning was better than 6 m. The integrity term for horizontal protection level and vertical protection level parameters in the flight test was below 16 m.

The paper presents only the application of GPS/GLONASS observations in aviation, without satellite data from other navigation systems.

The presented research method can be used in an aircraft based augmentation system in Polish aviation.

The paper is addressed to persons who work in aviation and air transport.

The paper presents the SPP method as a satellite technique for the recovery of an aircraft position in an aviation test.

Global positioning system (GPS) kinematic positioning suffers from performance degradation in constrained environments such as urban canyons, which then restricts the application of high-precision vehicle positioning and navigation within the city. In December 2012, the BeiDou Navigation Satellite System (BDS) regional service was announced, and the combined BDS/GPS kinematic positioning has been enabled in the Asia-Pacific area. Previous studies have mainly focused on the performance evaluations of combined BDS/GPS static positioning. Not much work has been performed for kinematic vehicle positioning under constrained observation conditions. This study aims to analyze the performance of BDS/GPS kinematic vehicle positioning in various conditions.

In this study, three vehicle experiments under three observation conditions, an open suburban area, a less dense non-central urban area and a dense central urban area, are investigated using both the code-based differential global navigation satellite system (DGNSS) and phase-based real-time kinematic (RTK) modes. The comparison between combined BDS/GPS and GPS-only vehicle positioning solutions is conducted in terms of positioning availability and positioning precision.

Numerical results show that the combined BDS/GPS system significantly outperforms the GPS-only system under poor observation conditions, whereas the improvement was less significant under good observation conditions.

Thus, this paper studies the performance of combined BDS/GPS kinematic relative positioning under various observation conditions.

The purpose of this paper is to present the problem of implementation of the differential global navigation satellite system (DGNSS) differential technique for aircraft accuracy positioning. The paper particularly focuses on identification and an analysis of the accuracy of aircraft positioning for the DGNSS measuring technique.

The investigation uses the DGNSS method of positioning, which is based on using the model of single code differences for global navigation satellite system (GNSS) observations. In the research experiment, the authors used single-frequency code observations in the global positioning system (GPS)/global navigation satellite system (GLONASS) system from the on-board receiver Topcon HiperPro and the reference station REF1 (reference station for the airport military EPDE in Deblin in south-eastern Poland). The geodetic Topcon HiperPro receiver was installed in Cessna 172 plane in the aviation test. The paper presents the new methodology in the DGNSS solution in air navigation. The aircraft position was estimated using a “weighted mean” scheme for differential global positioning system and differential global navigation satellite system solution, respectively. The final resultant position of aircraft was compared with precise real-time kinematic – on the fly solution.

In the investigations it was specified that the average accuracy of positioning the aircraft Cessna 172 in the geocentric coordinates XYZ equals approximately: +0.03 ÷ +0.33 m along the x-axis, −0.02 ÷ +0.14 m along the y-axis and approximately +0.02 ÷ −0.15 m along the z-axis. Moreover, the root mean square errors determining the measure of the accuracy of positioning of the Cessna 172 for the DGNSS differential technique in the geocentric coordinates XYZ, are below 1.2 m.

In research, the data from GNSS onboard receiver and also GNSS reference receiver are needed. In addition, the pseudo-range corrections from the base stations were applied in the observation model of the DGNSS solution.

The presented research method can be used in a ground based augmentation system (GBAS) augmentation system, whereas the GBAS system is still not applied in Polish aviation.

The paper is destined for people who work in the area of aviation and air transport.

The study presents the DGNSS differential technique as a precise method for recovery of aircraft position in civil aviation and this method can be also used in the positioning of aircraft based on GPS and GLONASS code observations.

The purpose of this paper is based on implementation of Global Navigation Satellite System (GNSS) technique in civil aviation for recovery of aircraft position using Single Point Positioning (SPP) method in kinematic mode.

The aircraft coordinates in ellipsoidal frame were obtained based on Global Positioning System (GPS) code observations for SPP method. The numerical computations were executed in post-processing mode in the Aircraft Positioning Software (APS) package. The mathematical scheme of equation observation of SPP method was solved using least square estimation in stochastic processing. In the experiment, airborne test using Cessna 172 aircraft on September 07, 2011 in the civil aerodrome in Mielec was realized. The aircraft position was recovery using observations data from Topcon HiperPro dual-frequency receiver with interval of 1 second.

In this paper, the average value of standard deviation of aircraft position is about 0.8 m for Latitude, 0.7 m for Longitude and 1.5 m for ellipsoidal height, respectively. In case of the Mean Radial Spherical Error (MRSE) parameter, the average value equals to 1.8 m. The standard deviation of receiver clock bias was presented in this paper and the average value amounts to 34.4 ns. In this paper, the safety protection levels of Horizontal Protection Level (HPL) and Vertical Protection Level (VPL) were also showed and described.

In this paper, the analysis of aircraft positioning is focused on application the least square estimation in SPP method. The Kalman filtering operation can be also applied in SPP method for designation the position of the aircraft.

The SPP method can be applied in civil aviation for designation the position of the aircraft in Non-Precision Approach (NPA) GNSS procedure at the landing phase. The typical accuracy of aircraft position is better than 220 m for lateral navigation in NPA GNSS procedure. The limit of accuracy of aircraft position in vertical plane in NPA GNSS procedure is not available.

This paper is destined for people who works in the area of aviation and air transport.

The work presents that SPP method as a universal technique for recovery of aircraft position in civil aviation, and this method can be also used in positioning of aircraft based on Global Navigation Satellite System (GLONASS) code observations.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

This paper aims to find methods to enhance position estimates for mobile terminals by cooperating with each other.

The main methods used are, on the one hand, mathematical modelling of the system, drone mobility, communication and positioning errors, and on the other hand, detailed discrete event simulation, which the author uses to evaluate the positioning errors. In the simulation runs, important parameters like signal speed, terminal velocity, area size and error correlation were varied. The author details the influence of these parameters on the theoretically possible error enhancement with respect to the traditional non-cooperative method.

Simulation results show that using cooperation is useful and can indeed significantly enhance the accuracy of position estimates, even in difficult situations. However, there are limits and the accuracy cannot always be enhanced.

Future research might use more sophisticated processing methods to further enhance position estimates. Limitations are given by the use of discrete time models in an inherently continuous system. Discretization errors are, however, kept low by using small time steps.

It has been shown that the positioning of drone swarms can be significantly enhanced once drones cooperate with each other. This might improve maneuverability of drones in all situations where drone swarms are used.

It has been proven by using simulation that cooperative positioning can yield positioning enhancements, even in difficult situations, when using wireless communication. In this light, future research can come up with practical implementations of such a cooperative approach.

The Department of Defence of the United States is in the process of implementing a satellite‐based navigation system called Navstar GPS (Global Positioning System). This system will have 24 satellites orbiting in three different orbits, with 8 satellites in each. Full implementation is planned for the mid to late 1980s. Partial use of the system should be possible commencing in the early 1980s. GPS can provide many unique features of particular benefit to helicopters, such as highly accurate airborne area navigation (RNAV) capability; accurate approach and landing guidance solely by reference to the airborne RNAV system; ability to function on a worldwide basis without the need for ground based navigation aids; unlimited capacity. Numerous benefits in addition to highly accurate navigation will accrue from civil application of GPS, including capability for automatic position reporting and air‐to‐air separation assurance. Cost benefits make application of GPS to civil aircraft in general, and particularly helicopters, highly attractive.

Until now, air navigation systems have mainly relied on global navigation satellite systems (GNSS) on the worldwide spread global positioning system. However, the so-called GNSS-denied environments open a new research line which pursues the development of alternative technologies which will cover this gap in positioning systems’ services.

This paper presents the possibility of using positioning systems based on global system for mobile communications (GSM) signal. This approach developed in a standalone device will provide real-time information. The presented algorithm pursues a new methodology for providing useful information.

Among all the different technologies aimed at giving a navigation solution in the absence of any kind of GNSS in which this paper is based, it advocates for the use of the signals of opportunity, particularly the usage of GSM.

Technology is currently immersed in an era of continuous progress and expansion of navigation systems. These are evolving toward high performance systems, offering precise, efficient and safe air navigation. In addition, the growing demand for unmanned aerial vehicles increases the level of exigency on this activity even more. Therefore, in the context of the development of unmanned navigation technologies, the aim is to implement positioning systems that will allow high precision even in though environments.

Referencing the SIMless concept, a SIM-free system is described in this paper. The SIM-free system is supported by open data bases and permits the positioning based on the information sniffed from the signals broadcast by a set of several nearby base station of the GSM network. Hence, it provides same and in some cases even better accuracies than the already developed techniques, not being necessary to synchronize the link between the mobile terminal and the base station transceiver (BTS).

Large-scale and precise three-dimensional (3D) map play an important role in autonomous driving and robot positioning. However, it is difficult to get accurate poses for mapping. On one hand, the global positioning system (GPS) data are not always reliable owing to multipath effect and poor satellite visibility in many urban environments. In another hand, the LiDAR-based odometry has accumulative errors. This paper aims to propose a novel simultaneous localization and mapping (SLAM) system to obtain large-scale and precise 3D map.

The proposed SLAM system optimally integrates the GPS data and a LiDAR odometry. In this system, two core algorithms are developed. To effectively verify reliability of the GPS data, VGL (the abbreviation of Verify GPS data with LiDAR data) algorithm is proposed and the points from LiDAR are used by the algorithm. To obtain accurate poses in GPS-denied areas, this paper proposes EG-LOAM algorithm, a LiDAR odometry with local optimization strategy to eliminate the accumulative errors by means of reliable GPS data.

On the KITTI data set and the customized outdoor data set, the system is able to generate high-precision 3D map in both GPS-denied areas and areas covered by GPS. Meanwhile, the VGL algorithm is proved to be able to verify reliability of the GPS data with confidence and the EG-LOAM outperform the state-of-the-art baselines.

A novel SLAM system is proposed to obtain large-scale and precise 3D map. To improve the robustness of the system, the VGL algorithm and the EG-LOAM are designed. The whole system as well as the two algorithms have a satisfactory performance in experiments.