scholarly journals Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

2018 ◽  
Vol 10 (7) ◽  
pp. 1157 ◽  
Author(s):  
Zhetao Zhang ◽  
Bofeng Li ◽  
Yunzhong Shen ◽  
Yang Gao ◽  
Miaomiao Wang
Keyword(s):  
Real Time ◽  
Weighting Function ◽  
Density Ratio ◽  
Signal Propagation ◽  
Urban Environments ◽  
Equal Weight ◽  
Noise Power ◽  
Site Specific ◽  
Gnss Positioning ◽  
Adaptive Weighting

In Global Navigation Satellite System (GNSS) positioning, observation precisions are frequently impacted by the site-specific unmodeled errors, especially for the code observations that are widely used by smart phones and vehicles in urban environments. The site-specific unmodeled errors mainly refer to the multipath and other space loss caused by the signal propagation (e.g., non-line-of-sight reception). As usual, the observation precisions are estimated by the weighting function in a stochastic model. Only once the realistic weighting function is applied can we obtain the precise positioning results. Unfortunately, the existing weighting schemes do not fully take these site-specific unmodeled effects into account. Specifically, the traditional weighting models indirectly and partly reflect, or even simply ignore, these unmodeled effects. In this paper, we propose a real-time adaptive weighting model to mitigate the site-specific unmodeled errors of code observations. This unmodeled-error-weighted model takes full advantages of satellite elevation angle and carrier-to-noise power density ratio (C/N0). In detail, elevation is taken as a fundamental part of the proposed model, then C/N0 is applied to estimate the precision of site-specific unmodeled errors. The principle of the second part is that the measured C/N0 will deviate from the nominal values when the signal distortions are severe. Specifically, the template functions of C/N0 and its precision, which can estimate the nominal values, are applied to adaptively adjust the precision of site-specific unmodeled errors. The proposed method is tested in single-point positioning (SPP) and code real-time differenced (RTD) positioning by static and kinematic datasets. Results indicate that the adaptive model is superior to the equal-weight, elevation and C/N0 models. Compared with these traditional approaches, the accuracy of SPP and RTD solutions are improved by 35.1% and 17.6% on average in the dense high-rise building group, as well as 11.4% and 11.9% on average in the urban-forested area. This demonstrates the benefit to code-based positioning brought by a real-time adaptive weighting model as it can mitigate the impacts of site-specific unmodeled errors and improve the positioning accuracy.

scholarly journals An SVM Based Weight Scheme for Improving Kinematic GNSS Positioning Accuracy with Low-Cost GNSS Receiver in Urban Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7265
Author(s):  
Zhitao Lyu ◽  
Yang Gao
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Urban Environments ◽  
Least Square ◽  
Single Frequency ◽  
Line Of Sight ◽  
Support Vector ◽  
Positioning Accuracy ◽  
Gnss Receiver ◽  
Gnss Positioning

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.

scholarly journals Site-by-site tracking of signal transduction in an azidophenyalanine-labeled bacteriophytochrome with step-scan FTIR spectroscopy

2021 ◽  
Author(s):  
Moona Kurttila ◽  
Brigitte Stucki-Buchli ◽  
Jessica Rumfeldt ◽  
Lea Schroeder ◽  
Heikki Häkkänen ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Ftir Spectroscopy ◽  
Real Time ◽  
Signal Propagation ◽  
Site Specific

Signal propagation in photosensory proteins is a complex and multidimensional event. Unraveling such mechanisms site-specifically in real time is an eligible but a challenging goal. Here, we elucidate the site-specific...

scholarly journals Conditioning and PPP processing of smartphone GNSS measurements in realistic environments

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Ganga Shinghal ◽  
Sunil Bisnath
Keyword(s):  
Single Point ◽  
A Priori ◽  
Density Ratio ◽  
Satellite System ◽  
Quality Parameters ◽  
Urban Environments ◽  
Dual Frequency ◽  
Missing Measurements ◽  
Data Gaps ◽  
Point Positioning

AbstractSmartphones typically compute position using duty-cycled Global Navigation Satellite System (GNSS) L1 code measurements and Single Point Positioning (SPP) processing with the aid of cellular and other measurements. This internal positioning solution has an accuracy of several tens to hundreds of meters in realistic environments (handheld, vehicle dashboard, suburban, urban forested, etc.). With the advent of multi-constellation, dual-frequency GNSS chips in smartphones, along with the ability to extract raw code and carrier-phase measurements, it is possible to use Precise Point Positioning (PPP) to improve positioning without any additional equipment. This research analyses GNSS measurement quality parameters from a Xiaomi MI 8 dual-frequency smartphone in varied, realistic environments. In such environments, the system suffers from frequent phase loss-of-lock leading to data gaps. The smartphone measurements have low and irregular carrier-to-noise (C/N0) density ratio and high multipath, which leads to poor or no positioning solution. These problems are addressed by implementing a prediction technique for data gaps and a C/N0-based stochastic model for assigning realistic a priori weights to the observables in the PPP processing engine. Using these conditioning techniques, there is a 64% decrease in the horizontal positioning Root Mean Square (RMS) error and 100% positioning solution availability in sub-urban environments tested. The horizontal and 3D RMS were 20 cm and 30 cm respectively in a static open-sky environment and the horizontal RMS for the realistic kinematic scenario was 7 m with the phone on the dashboard of the car, using the SwiftNav Piksi Real-Time Kinematic (RTK) solution as reference. The PPP solution, computed using the YorkU PPP engine, also had a 5–10% percentage point more availability than the RTK solution, computed using RTKLIB software, since missing measurements in the logged file cause epoch rejection and a non-continuous solution, a problem which is solved by prediction for the PPP solution. The internal unaided positioning solution of the phone obtained from the logged NMEA (The National Marine Electronics Association) file was computed using point positioning with the aid of measurements from internal sensors. The PPP solution was 80% more accurate than the internal solution which had periodic drifts due to non-continuous computation of solution.

scholarly journals Robustness against Chirp Signal Interference of On-Board Vehicle Geodetic and Low-Cost GNSS Receivers

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5257
Author(s):  
Franc Dimc ◽  
Polona Pavlovčič-Prešeren ◽  
Matej Bažec
Keyword(s):  
Interference Mitigation ◽  
Low Cost ◽  
Density Ratio ◽  
Autonomous Driving ◽  
Signal Interference ◽  
Noise Power ◽  
Reference Base ◽  
Noise Power Spectral Density ◽  
Processing Abilities ◽  
Gnss Receivers

Robust autonomous driving, as long as it relies on satellite-based positioning, requires carrier-phase-based algorithms, among other types of data sources, to obtain precise and true positions, which is also primarily true for the use of GNSS geodetic receivers, but also increasingly true for mass-market devices. The experiment was conducted under line-of-sight conditions on a straight road during a period of no traffic. The receivers were positioned on the roof of a car travelling at low speed in the presence of a static jammer, while kinematic relative positioning was performed with the static reference base receiver. Interference mitigation techniques in the GNSS receivers used, which were unknown to the authors, were compared using (a) the observed carrier-to-noise power spectral density ratio as an indication of the receivers’ ability to improve signal quality, and (b) the post-processed position solutions based on RINEX-formatted data. The observed carrier-to-noise density generally exerts the expected dependencies and leaves space for comparisons of applied processing abilities in the receivers, while conclusions on the output data results comparison are limited due to the non-synchronized clocks of the receivers. According to our current and previous results, none of the GNSS receivers used in the experiments employs an effective type of complete mitigation technique adapted to the chirp jammer.

scholarly journals Analytical Models for the Computation of Error Probability of Multi-Level Phase Shift Keying Modulation Scheme

2021 ◽  
Vol 4 (1) ◽  
pp. 13-20
Author(s):  
Isaac A. E. ◽  
Dike H.U.
Keyword(s):  
Phase Shift ◽  
Error Probability ◽  
Error Function ◽  
Density Ratio ◽  
Analytical Models ◽  
Modulation Scheme ◽  
Noise Power ◽  
Phase Shift Keying ◽  
Shift Keying ◽  
Multi Level

In this paper, analytical models for the computation of error probability (BER) of the Multi-level Phase Shift Keying (MPSK) modulation scheme is presented. Analytical models for computing MPSK bit error probability based on Q function, error function (erf) and complementary error function (erfc) are presented. Also, an analytical model for computing the symbol error rate for MPSK is presented. Furthermore, a generalized analytical expression for BER as a function of modulation order (M) and energy per bit to noise power density ratio (Eb/No) is presented. The BER was computed for various values of M (2 ≤ M ≤ 256) and Eb/No (0 dB ≤ Eb/No ≤ 14 Db). The results showed that at Eb/No =12 dB, a BER of 9.006E-09 is realized for M =2 and M =4 whereas BER of 1.056E-01 is realized for M = 256. Also, for the same M = 2 , the value of BER decreased from 1.2501E-02 at Eb/No = 4 dB to 9.0060E-09at Eb/No =12 dB. Generally, the results showed that for the MPSK modulation scheme, for a given value of Eb/No, the lower modulation order (M) has a lower BER and for a given modulation order, (M) the BER decreases as Eb/No increases.

scholarly journals Waterborne illness and injury: a feasibility study of a site-specific predictive model for beach water quality at Beachway Park in the City of Burlington

2021 ◽  
Author(s):  
Ramien Sereshk
Keyword(s):  
Water Quality ◽  
Predictive Model ◽  
Real Time ◽  
Site Specific ◽  
E Coli ◽  
Time Basis ◽  
A Site ◽  
Persistence Model ◽  
Beach Water Quality ◽  
Beach Water

It is commonly assumed that the persistence model, using day-old monitoring results, will provide accurate estimates of real-time bacteriological concentrations in beach water. However, the persistence model frequently provides incorrect results. This study: 1. develops a site-specific predictive model, based on factors significantly influencing water quality at Beachway Park; 2. determines the feasibility of the site-specific predictive model for use in accurately predicting near real-time E. coli levels. A site-specific predictive model, developed for Beachway Park, was evaluated and the results were compared to the persistence model. This critical performance evaluation helped to identify the inherent inaccuracy of the persistence model for Beachway Park, which renders it an unacceptable approach for safeguarding public health from recreational water-borne illnesses. The persistence model, supplemented with a site-specific predictive model, is recommended as a feasible method to accurately predict bacterial levels in water on a near real-time basis.

Real-Time Pedestrian Recognition in Urban Environments

2011 ◽  
pp. 139-147 ◽  
Author(s):  
Basam Musleh ◽  
Arturo de la Escalera ◽  
José Maria Armingol
Keyword(s):  
Real Time ◽  
Urban Environments
Sign in / Sign up

Export Citation Format

Share Document