A Novel Multipath Mitigation Technique for GNSS Signals in Urban Scenarios

Kumar, Anil; Singh, Arun Kumar

doi:10.1109/tvt.2019.2962919

Cited by 16 publications

(7 citation statements)

References 21 publications

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“…It can be seen from equation (2) that Δf m (t) depends on the Doppler frequency difference (Δw m − Δw 0 ); when it changes rapidly with time, the relative speed between the ground receiving antenna and the satellite will be relatively fast, and Δf m (t) will be larger.…”

Section: Fading Frequency Of the Multipath Signalmentioning

confidence: 99%

“…e satellite navigation system has become one of the most important technical means in modern navigation and positioning measurement [1,2]. To pursue more accurate positioning results, it is necessary to analyze the reasons that affect the accuracy of a satellite navigation system and take targeted measures to reduce and correct the relevant errors and obtain a better positioning performance [3,4].…”

Section: Introductionmentioning

confidence: 99%

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A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS

Zhou

Lian

2021

Mobile Information Systems

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In the Global Navigation Satellite System (GNSS), the multipath error affected by many aspects is the main error source that affects satellite navigation, and it is difficult to establish a much more accurate model to analyze it. Based on the ground multipath reflection model, it firstly deeply studies the influence of GNSS satellite orbit parameters on multipath fading frequency and establishes a multipath signal model related to satellite orbit parameters. Secondly, the influence of carrier phase cycle slip, receiver clock adjustment, and GNSS satellite orbit on multiparameter- (MP-) combined observations is analyzed in detail based on the measured data. Finally, aiming at the common phenomenon of code-carrier divergence in the Beidou system, the elevation-based pseudorange correction model and a sidereal filtering are built to correct the MP errors; experiments with measured data show that there is a fluctuation range reduction of 35.7% after sidereal filtering when the receiver reaches a steady state.

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Section: Fading Frequency Of the Multipath Signalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS

Zhou

Lian

2021

Mobile Information Systems

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“…The cost and bulky size of the antennas limit the applications for ITS in urban environments, however. Signal processing methods can be used to reduce certain kinds of multipath error by improving the form of the receiver correlator structure design or correlator function, but they are not able to address NLOS effects (Yang 2016;Chen et al 2020;He et al 2020;Kumar and Singh 2020;Qi et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Pseudorange error prediction for adaptive tightly coupled GNSS/IMU navigation in urban areas

et al. 2021

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The integration of global navigation satellite systems (GNSS) and inertial measurement unit (IMU) with the Kalman filter is widely used to enhance the availability of positioning in urban areas for many intelligent transport system (ITS) applications. In the traditional Kalman filter, the GNSS measurement noise is fixed based on factors determined a priori, instead of reflecting the impact of the surrounding environment on the received GNSS signal. This has the effect of degrading position accuracy and the a posteriori quality indicators. To address this issue, we propose a new measurement noise covariance update scheme, with the adaptive indicator generated from pseudorange error prediction results, for a tightly coupled GNSS/ IMU navigation system in urban areas. Specifically, the pseudorange errors are predicted by means of an ensemble bagged regression tree model accounting for signal strength, satellite elevation angle and coordinate information. The urban experimental results show that the proposed algorithm provides a 3D accuracy of 9.21 m, with an improvement of 55% and 15%, respectively, over the traditional fixed covariance extended Kalman filter (EKF)-based fusion and EKF-based fusion with pseudorange error correction.

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“…Hence, multistatic radar can be used in many scenarios, such as in urban centres [18], indoors [19] and at low angles [20]. However, in these scenarios, there are always many different possible paths, which cannot be ignored since they depend on the target [21, 22]. In traditional detection methods, such multiple paths are regarded as an unfavourable influence to be eliminated [23, 24].…”

Section: Introductionmentioning

confidence: 99%

Time reversal detection in a multistatic radar system with a varying environment

Zhang

Chen

Yang

2021

IET Radar Sonar & Navi

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Multistatic radar has the advantage of spatial diversity, but its detection performance is decreased in dense multipath scattering environments. This problem can be solved by using the time reversal (TR) technique to take advantage of the multipath effect to improve target detection; however, this usually requires a stationary channel response that is difficult to achieve in practice. This article studies a TR detection algorithm for a multistatic radar system in a varying multipath channel environment. We establish a varying channel response model and derive a time reversal likelihood ratio test (TR-LRT) detector to utilise the characteristics of multiple paths when the multipath environment is changing during the detection process. We use Monte Carlo simulations and theoretical analysis to show the superior performance of the proposed TR detector compared with a conventional detector. Our proposed TR-LRT detector shows good robustness to environmental variations. Simulation results show that better detection results are achieved in a more severe multipath scattering environment.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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A Novel Multipath Mitigation Technique for GNSS Signals in Urban Scenarios

Cited by 16 publications

References 21 publications

A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS

A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS

Pseudorange error prediction for adaptive tightly coupled GNSS/IMU navigation in urban areas

Time reversal detection in a multistatic radar system with a varying environment

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