scholarly journals Optimal Particle Filter Weight for Bayesian Direct Position Estimation in a GNSS Receiver

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2736 ◽  
Author(s):  
Jürgen Dampf ◽  
Kathrin Frankl ◽  
Thomas Pany
Keyword(s):  
Numerical Evaluation ◽  
Probability Distributions ◽  
Satellite System ◽  
Position Estimation ◽  
Logarithmic Scale ◽  
Satellite Clock ◽  
Signal Model ◽  
Stochastic Signal ◽  
Global Navigation Satellite ◽  
Particle Weight

Direct Position Estimation (DPE) is a rather new Global Navigation Satellite System (GNSS) technique to estimate the user position, velocity and time (PVT) directly from correlation values of the received GNSS signal with receiver internal replica signals. If combined with Bayesian nonlinear filters—like particle filters—the method allows for coping with multi-modal probability distributions and avoids the linearization step to convert correlation values into pseudoranges. The measurement update equation (particle weight update) is derived from a standard GNSS signal model, but we show that it cannot be used directly in a receiver implementation. The numerical evaluation of the formulas needs to be carried out in a logarithmic scale including various normalizations. Furthermore, the residual user range errors (coming from orbit, satellite clock, multipath or ionospheric errors) need to be included from the very beginning in the stochastic signal model. With these modifications, sensible probability functions can be derived from the GNSS multi-correlator values. The occurrence of multipath yields a natural widening of the probability density function. The approach is demonstrated with simulated and real-world

scholarly journals Many Ways Lead to the Goal—Possibilities of Autonomous and Infrastructure-Based Indoor Positioning

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 397
Author(s):  
Hossein Shoushtari ◽  
Thomas Willemsen ◽  
Harald Sternberg
Keyword(s):  
Mobile Networks ◽  
Dead Reckoning ◽  
Simulated Data ◽  
Minimum Cost ◽  
Cost Effective ◽  
Satellite System ◽  
Position Estimation ◽  
Robust Solution ◽  
Position Data ◽  
Global Navigation Satellite

There are many ways to navigate in Global Navigation Satellite System-(GNSS) shaded areas. Reliable indoor pedestrian navigation has been a central aim of technology researchers in recent years; however, there still exist open challenges requiring re-examination and evaluation. In this paper, a novel dataset is used to evaluate common approaches for autonomous and infrastructure-based positioning methods. The autonomous variant is the most cost-effective realization; however, realizations using the real test data demonstrate that the use of only autonomous solutions cannot always provide a robust solution. Therefore, correction through the use of infrastructure-based position estimation based on smartphone technology is discussed. This approach invokes the minimum cost when using existing infrastructure, whereby Pedestrian Dead Reckoning (PDR) forms the basis of the autonomous position estimation. Realizations with Particle Filters (PF) and a topological approach are presented and discussed. Floor plans and routing graphs are used, in this case, to support PDR positioning. The results show that the positioning model loses stability after a given period of time. Fifth Generation (5G) mobile networks can enable this feature, as well as a massive number of use-cases, which would benefit from user position data. Therefore, a fusion concept of PDR and 5G is presented, the benefit of which is demonstrated using the simulated data. Subsequently, the first implementation of PDR with 5G positioning using PF is carried out.

scholarly journals Improving the Performance of Multi-GNSS (Global Navigation Satellite System) Ambiguity Fixing for Airborne Kinematic Positioning over Antarctica

2019 ◽  
Vol 11 (8) ◽  
pp. 992
Author(s):  
Li ◽  
Xu ◽  
Flechtner ◽  
Förste ◽  
Lu ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Satellite System ◽  
Integer Ambiguity ◽  
Navigation Satellite ◽  
Satellite Clock ◽  
Kinematic Positioning ◽  
Ambiguity Fixing ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Orbit Errors

Conventional relative kinematic positioning is difficult to be applied in the polar region of Earth since there is a very sparse distribution of reference stations, while precise point positioning (PPP), using data of a stand-alone receiver, is recognized as a promising tool for obtaining reliable and accurate trajectories of moving platforms. However, PPP and its integer ambiguity fixing performance could be much degraded by satellite orbits and clocks of poor quality, such as those of the geostationary Earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS), because temporal variation of orbit errors cannot be fully absorbed by ambiguities. To overcome such problems, a network-based processing, referred to as precise orbit positioning (POP), in which the satellite clock offsets are estimated with fixed precise orbits, is implemented in this study. The POP approach is validated in comparison with PPP in terms of integer ambiguity fixing and trajectory accuracy. In a simulation test, multi-GNSS (global navigation satellite system) observations over 14 days from 136 globally distributed MGEX (the multi-GNSS Experiment) receivers are used and four of them on the coast of Antarctica are processed in kinematic mode as moving stations. The results show that POP can improve the ambiguity fixing of all system combinations and significant improvement is found in the solution with BDS, since its large orbit errors are reduced in an integrated adjustment with satellite clock offsets. The four-system GPS+GLONASS+Galileo+BDS (GREC) fixed solution enables the highest 3D position accuracy of about 3.0 cm compared to 4.3 cm of the GPS-only solution. Through a real flight experiment over Antarctica, it is also confirmed that POP ambiguity fixing performs better and thus can considerably speed up (re-)convergence and reduce most of the fluctuations in PPP solutions, since the continuous tracking time is short compared to that in other regions.

scholarly journals Validation of the EGSIEM-REPRO GNSS Orbits and Satellite Clock Corrections

2020 ◽  
Vol 12 (14) ◽  
pp. 2322 ◽  
Author(s):  
Andreja Sušnik ◽  
Andrea Grahsl ◽  
Daniel Arnold ◽  
Arturo Villiger ◽  
Rolf Dach ◽  
...  
Keyword(s):  
Orbit Determination ◽  
Precise Orbit Determination ◽  
Satellite System ◽  
Satellite Orbits ◽  
Satellite Clock ◽  
Gps Satellites ◽  
Glonass Satellite ◽  
Global Navigation Satellite ◽  
Gravity Recovery ◽  
First Time

In the framework of the European Gravity Service for Improved Emergency Management (EGSIEM) project, consistent sets of state-of-the-art reprocessed Global Navigation Satellite System (GNSS) orbits and satellite clock corrections have been generated. The reprocessing campaign includes data starting in 1994 and follows the Center for Orbit Determination in Europe (CODE) processing strategy, in particular exploiting the extended version of the empirical CODE Orbit Model (ECOM). Satellite orbits are provided for Global Positioning System (GPS) satellites since 1994 and for Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) since 2002. In addition, a consistent set of GPS satellite clock corrections with 30 s sampling has been generated from 2000 and with 5 s sampling from 2003 onwards. For the first time in a reprocessing scheme, GLONASS satellite clock corrections with 30 s sampling from 2008 and 5 s from 2010 onwards were also generated. The benefit with respect to earlier reprocessing series is demonstrated in terms of polar motion coordinates. GNSS satellite clock corrections are validated in terms of completeness, Allan deviation, and precise point positioning (PPP) using terrestrial stations. In addition, the products herein were validated with Gravity Recovery and Climate Experiment (GRACE) precise orbit determination (POD) and Satellite Laser Ranging (SLR). The dataset is publicly available.

scholarly journals Investigation of Tightly Combined Single-Frequency and Single-Epoch Precise Positioning Using Multi-GNSS Data

2020 ◽  
Vol 12 (2) ◽  
pp. 285
Author(s):  
Chenlong Deng ◽  
Qian Liu ◽  
Xuan Zou ◽  
Weiming Tang ◽  
Jianhui Cui ◽  
...  
Keyword(s):  
Satellite System ◽  
Position Estimation ◽  
Single Frequency ◽  
Navigation Satellite ◽  
Typical Situation ◽  
Practical Algorithms ◽  
Ambiguity Fixing ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Tc Model

The loose combination (LC) and the tight combination (TC) are two different models in the combined processing of four global navigation satellite systems (GNSSs). The former is easy to implement but may be unusable with few satellites, while the latter should cope with the inter-system bias (ISB) and is applicable for few tracked satellites. Furthermore, in both models, the inter-frequency bias (IFB) in the GLObal NAvigation Satellite System (GLONASS) system should also be removed. In this study, we aimed to investigate the performance difference of ambiguity resolution and position estimation between these two models simultaneously using the single-frequency data of all four systems (GPS + GLONASS + Galileo + BeiDou Navigation Satellite System (BDS)) in three different environments, i.e., in an open area, with surrounding high buildings, and under a block of high buildings. For this purpose, we first provide the definition of ISB and IFB from the perspective of the hardware delays, and then propose practical algorithms to estimate the IFB rate and ISB. Thereafter, a comprehensive performance comparison was made between the TC and LC models. Experiments were conducted to simulate the above three observation environments: the typical situation and situations suffering from signal obstruction with high elevation angles and limited azimuths, respectively. The results show that in a typical situation, the TC and LC models achieve a similar performance. However, when the satellite signals are severely obstructed and few satellites are tracked, the float solution and ambiguity fixing rates in the LC model are dramatically decreased, while in the TC model, there are only minor declines and the difference in the ambiguity fixing rates can be as large as 30%. The correctly fixed ambiguity rates in the TC model also had an improvement of around 10%. Once the ambiguity was fixed, both models achieved a similar positioning accuracy.

scholarly journals Semantic VPS for Smartphone Localization in Challenging Urban Environments

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6137
Author(s):  
Max Jwo Lem Lee ◽  
Li-Ta Hsu ◽  
Hoi-Fung Ng
Keyword(s):  
Smart Cities ◽  
Satellite System ◽  
Urban Environments ◽  
Position Estimation ◽  
Information Modeling ◽  
Position Information ◽  
Precise Position ◽  
Segmented Images ◽  
Building Information ◽  
Global Navigation Satellite

Accurate smartphone-based outdoor localization systems in deep urban canyons are increasingly needed for various IoT applications. As smart cities have developed, building information modeling (BIM) has become widely available. This article, for the first time, presents a semantic Visual Positioning System (VPS) for accurate and robust position estimation in urban canyons where the global navigation satellite system (GNSS) tends to fail. In the offline stage, a material segmented BIM is used to generate segmented images. In the online stage, an image is taken with a smartphone camera that provides textual information about the surrounding environment. The approach utilizes computer vision algorithms to segment between the different types of material class identified in the smartphone image. A semantic VPS method is then used to match the segmented generated images with the segmented smartphone image. Each generated image contains position information in terms of latitude, longitude, altitude, yaw, pitch, and roll. The candidate with the maximum likelihood is regarded as the precise position of the user. The positioning result achieved an accuracy of 2.0 m among high-rise buildings on a street, 5.5 m in a dense foliage environment, and 15.7 m in an alleyway. This represents an improvement in positioning of 45% compared to the current state-of-the-art method. The estimation of yaw achieved accuracy of 2.3°, an eight-fold improvement compared to the smartphone IMU.

scholarly journals A Fast Acquisition Algorithm Overcoming Fuzz Problems for TDDM Spread Spectrum Signal

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Fang Liu ◽  
Yongxin Feng
Keyword(s):  
Spread Spectrum ◽  
Phase Error ◽  
Satellite System ◽  
Position Estimation ◽  
Frequency Error ◽  
Next Generation ◽  
Error Message ◽  
Fast Acquisition ◽  
Global Navigation Satellite ◽  
Time Division

TDDM (time division data modulation) technique will be used in the next generation GNSS (global navigation satellite system) to improve processing performance and to reduce inter-GNSS interference; however, the emergence of TDDM signal causes the estimation frequency and message reversal fuzz problems in the acquisition process of a GNSS receiver. At present, the traditional acquisition methods have some limitations and shortcomings. Therefore, aiming at the unique characteristics of TDDM signal, a fast acquisition algorithm is proposed to overcome these fuzz problems in this paper. In the proposed algorithm, three stages are obtained by some key technologies, which are theI-Qfrequency compensation, superposition processing, subsection processing, and reversion position estimation. Besides, the algorithm is simulated from carrier frequency error, code phase error, message inversion error, and processing speed. Theoretical and simulation results show that the new algorithm can quickly overcome the fuzz problems, and the new algorithm is better than the existing algorithm in the speed and accuracy, which demonstrates that this new algorithm is an effective search scheme for the next generation GNSS signals.

scholarly journals The Single-Shore-Station-Based Position Estimation Method of an Automatic Identification System

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1590 ◽  
Author(s):  
Yi Jiang ◽  
Kai Zheng
Keyword(s):  
Estimation Method ◽  
Satellite System ◽  
Position Estimation ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Shore Station ◽  
Position Data ◽  
Positioning Method ◽  
Global Navigation Satellite

In order to overcome the vulnerability of the Global Navigation Satellite System (GNSS), the International Maritime Organization (IMO) initiated the ranging mode (R-Mode) of the automatic identification system (AIS) to provide resilient position data. As the existing AIS is a communication system, the number of shore stations as reference stations cannot satisfy positioning requirements. Especially in the area near a shore station, it is very common that a vessel can only receive signals from one shore station, where the traditional positioning method cannot be used. A novel position estimation method using multiple antennas on shipborne equipment is proposed here, which provides a vessel’s position even though the vessel can only receive signals from a single shore station. It is beneficial for solving positioning issues in proximity to the coast. Further, as the distances between different antennas to the shore station are not sufficiently independent, the positioning matrix can easily be near singularity or ill-conditioned; thus, an effective position solving method is derived. Furthermore, the proposed method is verified and evaluated in different scenarios by numerical simulation. We assessed the influencing factors of positioning performance, such as the vessel’s heading angle, the relative position, and the distances between the shore station and the vessel. The proposed method widely expands the application scope of the AIS R-Mode positioning system.

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