Smartphone-based GNSS/PDR integration navigation enhanced by measurements resilient adjustment under challenging scenarios

Understanding the advantage of Wi-Fi technology and its dependency in future, its applications on the positioning system in an indoor scenario, GPS being the most known positioning system has a drawback when it comes to the indoor environment. So to overcome difficulties in indoor LBS, a different algorithm is implemented in AP of Wi-Fi communication system to collect the data from the traffic which is connected through the SSID- Service Set Identifier. In this proposed work for crowdsourcing with the help of access point which is already in use for accessing the internet. The positioning system is developed using trilateration and linear regression which is accurate about 2-4 meters, also minimal time consumption is achieved due to the python platform used in position computation and its position detected can be used for crowdsourcing in which frequent visitor is detected as a frequent client since its application is more applicable in commercial purpose like advertising and marketing in the public areas.

Client Position Detection using Wi-Fi Technology

The detection of two-line element (TLE) outliers and space events play a crucial role in enhancing spatial situational awareness. Therefore, this paper addresses the issue of TLE outlier detection methods that often overlook the mutual influence of multiple factors. Hence, a Multivariate Gaussian Mixture Model (MGMM) is introduced to consider the interdependencies among various indicators. Additionally, a Multi-strategy Genetic Algorithm (MGA) is employed to adjust the complexity of the MGMM, allowing it to accurately learn the actual distribution of TLE data. Initially, the proposed method applies probabilistic fits to the predicted error rate changes for both the TLE semi-major axis and the orbital inclination. Chaos initialization, a posterior probability penalty, and local optimization iterations are subsequently integrated into the genetic algorithm. These enhancements aim to estimate the MGMM parameters, addressing issues related to poor robustness and the susceptibility of the MGMM to converge to local optima. The algorithm’s effectiveness is validated using TLE data from typical space targets. The results demonstrate that the optimized algorithm can efficiently detect outliers and maneuver events within complex TLE data. Notably, the comprehensive detection performance index, measured, using the F1 score, improved by 15.9% compared to the Gaussian mixture model. This significant improvement underscores the importance of the proposed method in bolstering the security of complex space environments. 

Two-Line Element Outlier and Space Event Detection Method Based on Multi-Strategy Genetic Algorithm

Low Earth Orbit (LEO) satellites are widely used in mobile communications. They can be used to provide navigation services by broadcasting navigation signals and augmentation information. However, it is extremely expensive to construct a mega constellation of LEO satellites equipped with navigation payloads. A better way would be making good use of the LEO communication satellites equipped with high-precision GNSS receivers. In this paper, we proposed a novel and low-cost Global Navigation Satellite System (GNSS) augmentation technique named “Real Time Kinematic (RTK) from space” for the LEO communication satellites. In the proposed algorithm, LEO satellites provide spatial datum for positioning users with their precise orbits. Through the communication link, users can obtain real-time augmentation information, including GNSS precise ephemeris, the onboard GNSS observations, centre of mass of LEO satellites, and the LEO satellites attitude quaternions. Using the augmentation information, user terminals can achieve precise positioning with fast ambiguity fixing. To validate the algorithm, we conduct experiments using simulated data and real-world data. The simulation experiments indicate that the GPS only solution needs around 35 seconds to get ambiguity fixed while GPS and BeiDou dual sytems take 37.1% less time. In terms of positioning accuracy, the GPS only solution has an 3D RMS (Root Mean Squared) of 1.93 cm while 1.48 cm for GPS + BDS. Real-world data experiments using GRACE-FO-C satellite and four IGS stations (ABMF, ABPO, AGGO and WUH2) show an average fixing time of 22.7 epochs. The average positioning errors in the east, north, and up directions are 2.4 cm, 2.6 cm, and 5.3 cm, respectively.

RTK from space: a novel and low-cost GNSS augmentation technique for LEO communication satellites

Zenith wet delay (ZWD) estimation is a key component for the global navigation satellite system (GNSS) meteorology. At present, the zenith hydrostatic delay can be computed with sufficient accuracy by means of empirical models, while the ZWD, which is induced by water vapor with the nature of highly spatio-temporal variability, is typically estimated as an unknown parameter in precise point positioning (PPP). Due to GNSS receiver noise and the system biases of GNSS receivers, the accuracy as well as the precision of ZWD estimates is limited. In this study, we propose a novel fusion model based on undifferenced GNSS pseudorange and carrier-phase observations for sites, which have several receivers connected to a single antenna or which are separated horizontally by only a few meters. By fusing GNSS measurements collected by multiple receivers on the observation level, our model can provide common ZWD estimates with a high temporal resolution, which can then be used for more accurate and reliable meteorologic applications on a local scale. According to results with simulated and real data, it is revealed that such combined ZWD estimates are superior to single receiver estimates in terms of precision and accuracy. On the other hand, it is confirmed that the estimation of a common ZWD parameter leads to an improvement in positioning accuracy and precision, especially in the vertical component.

Improving GNSS Meteorology by Fusing Measurements of Several Colocated Receivers on the Observation Level

Abstract The centimeter-level positioning accuracy of real-time kinematic (RTK) depends on correctly resolving integer carrier-phase ambiguities. To improve the success rate of ambiguity resolution and obtain reliable positioning results, an enhanced Kalman filtering procedure has been developed. Based on a posteriori residuals of measurements and state predictions, the measurement noise variance–covariance matrix for double-differenced measurements is adaptively estimated, rather than approximated by an empirical function which uses satellite elevation angle as input. Since, in real-world situations, unexpected outliers and carrier-phase outages can degrade the filter performance, a stochastic model based on robust Kalman filtering is proposed, for which the double-differenced measurement noise variance–covariance matrix is computed empirically with a modified version of the IGG (Institute of Geodesy and Geophysics) III method in order to detect and identify outliers. The performance of the proposed method is assessed by two tests, one with simulated data and one with real data. In addition, the performance of F-ratio and W-ratio tests as proxies for the success of ambiguity fixing is investigated. Experimental results reveal that the proposed method can improve the reliability and robustness of relative kinematic positioning for simulation scenarios as well as in a real urban test. 

/pdf/stochastic-modeling-with-robust-kalman-filter-for-real-time-3jjpurdm.pdf

Stochastic modeling with robust Kalman filter for real-time kinematic GPS single-frequency positioning

The current constellation of GLONASS uses frequency division multiple access (FDMA), meaning the code observations of different satellites have inter-frequency biases (IFB). The code IFB is usually included in the pseudo-range residuals when performing precise point positioning (PPP). However, it will affect the convergence of PPP when the value of code IFB is large. In this contribution, a GLONASS PPP algorithm considering the influence of pseudo-range IFB is presented. The unified model of the algorithm in the ionosphere-free combination PPP and original observation PPP is given. At the same time, the validity of this algorithm is verified through the GLONASS observation data. The results show that the algorithm can effectively weaken the influence of the code IFB and the convergence speed and residual distribution of the GLONASS PPP considering the influence of code IFB is better than traditional method.

GLONASS precise point positioning considering the influence of code inter-frequency biases

The ionospheric delay model is a reliable method to reduce the influence of ionospheric delay. The phase smoothed pseudorange observations are always used to construct ionospheric delay model. However, the accuracy of the constructed ionosphere model is affected by precision of phase smoothed pseudorange observations and the number of base stations. This contribution presents a construction method of ionospheric delay model with combined BDS phase and range observation. The observations of ionospheric delay is constructed by precise point positioning (PPP) with original observations. At the same time, the polynomial model is used to ionosphere modeling. Finally, the validity of this method is verified using BDS and GPS data. The bias of ionosphere model is less than 1 m and the standard deviation is better than 0.4 m.

The Construction Method of Ionospheric Delay Model with Combined BDS Phase and Range Observation

Galileo Satellite Navigation System has been put into trial operation at the end of 2016. Whether Galileo Satellite Navigation System can be used independently for navigation and positioning needs to be analyzed and evaluated because it is not yet in full constellation, especially the performance of Galileo Precision Point Positioning is worth studying. This paper evaluates the global positioning performance of Galileo Precision Point Positioning. The Galileo satellite visibility, average DOP value, convergence speed and positioning accuracy of PPP in different regions are evaluated by experiments with MGEX observation data. The experimental results show that in the initial operation stage of Galileo, the convergence speed of Galileo PPP is slower due to fewer visible satellites, but the positioning accuracy of static PPP is comparable to that of GPS PPP. At the same time, the positioning accuracy and convergence speed of GPS/Galileo PPP is better than that of Galileo PPP.

Performance Evaluation of Galileo Precise Point Positioning

Pseudo-code noise amplification theory of ionosphere-free combination is studied in this article, In allusion to the disadvantage of iono-free combination, The balance between the noise reduction and the incomplete elimination of ionospheric delay is finded. A new combination is proposed considering both the noise reduction and the ionospheric correction, which is called Iono-weak combination. According to the experiment, we reach the conclusion that the SPP result of ionosphere-weak combination is better than ionosphere-free combination with GPS data. The positioning accuracy of optimal combination can be increased about 15%. In allusion to the phenomenon that BDS ionosphere-weak combination can only improve the horizontal precision, the assumption of Total Group Delay (TGD) effect in BDS broadcast ephemeris is raised. The experiment result of BDS is consistent with GPS using ionosphere-weak combination without TGD correction. The rationality of the assumption is proved.

The Analysis of GPS/BDS Ionosphere-Weak Combination SPP Result

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