MP mitigation in GNSS positioning by GRU NNs and adaptive wavelet filtering

Li, Dengao; Zhang, Pei; Zhao, Jumin; Cheng, Jun; Zhao, Hongyan

doi:10.1049/iet-com.2018.5792

Cited by 6 publications

(5 citation statements)

References 21 publications

(29 reference statements)

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“…Finally, the new emerging trend in interference mitigation is the use of machine learning (ML) methods [ 45 , 46 ]. These methods promise good performance against interferences.…”

Section: Introductionmentioning

confidence: 99%

HDDM Hardware Evaluation for Robust Interference Mitigation

Garzia

Merwe

Rügamer

et al. 2020

Sensors

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Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art interference mitigation techniques. The high-rate DFT-based data manipulator (HDDM) is proposed as a possible solution to overcome their limitations. This paper presents a hardware implementation of the HDDM algorithm. The hardware HDDM module is integrated in three different receivers equipped with analog radio-frequency (RF) front-ends supporting signals with different dynamic range. The resource utilization and power consumption is evaluated for the three cases. The algorithm is compared to a low-end mass-market receiver and a high-end professional receiver with basic and sophisticated interference mitigation capabilities, respectively. Different type of interference are used to compare the mitigation capabilities of the receivers under test. Results of the HDDM hardware implementation achieve the similar or improved performance to the state of the art. With more complex interferences, like frequency hopping or pulsed, the HDDM shows even better performance.

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“…Finally, the new emerging trend in interference mitigation is the use of machine learning (ML) methods [ 45 , 46 ]. These methods promise good performance against interferences.…”

Section: Introductionmentioning

confidence: 99%

HDDM Hardware Evaluation for Robust Interference Mitigation

Garzia

Merwe

Rügamer

et al. 2020

Sensors

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“…Multipath error cannot be eliminated by the double-differenced technique and is difficult to parameterize, which severely restrict the high-precision GNSS positioning application. A correlation reconstruction algorithm for energy compensation under the BOC system is studied in [13]. A time-division multiplexing dual reference waveform multipath suppression algorithm for TMBOC signals is studied in [14].…”

Section: Literature Reviewmentioning

confidence: 99%

“…where the ionospheric delay 2cI can be modified with a double-frequency ionospheric correction method described in [13]. e carrier multipath error can be ignored, for its maximum multipath error is much smaller than that of code multipath error [14].…”

Section: Mp-combined Observationsmentioning

confidence: 99%

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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“…For example, Shin et al introduced a new filtering algorithm with ionosphere correction and combined DGPS to provide 1 m accuracy [16]; Geng et al proposed a three-thresholds and single-difference Hatch filter algorithm and combined Kalman filter to achieve sub-meter positioning accuracy using Android raw GNSS measurements without external augmentation corrections [17]. Other pseudorange multipath error mitigation methods have also been proven to improve positioning accuracy [18][19][20]. Although some smoothing/correction algorithms greatly reduce the pseudorange error, they are prone to failure when raw measurement quality is challenging.…”

Section: Introductionmentioning

confidence: 99%

Improving GNSS positioning performance of Android smart devices by a novel pseudorange correction method

Li¹,

Song²,

Li³

et al. 2023

Meas. Sci. Technol.

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To achieve high-precision GNSS positioning of smart devices, it is necessary to correct the pseudorange measurements, especially to reduce time-related errors. Traditional pseudorange smoothing methods fail to cope with measurement anomalies and do not consider the time correlation. Therefore, a time-correlated pseudorange correction (TCPC) method is proposed. The Mann-Kendall trend test and breakpoint detection are used to address data anomalies and pseudorange errors are estimated with an adaptive smoothing method. Using the proposed method, the GNSS receivers can improve the pseudorange accuracy and availability for better single-point positioning performance. The positioning errors are reduced by 10%−45% for different GNSS receivers. Moreover, the circular antenna motion mechanism is used to reduce the measurement correlation and enhance observability. Using the TCPC method in the smartphone antenna motion case, the improvement rates of positioning accuracies are 43%−76% and the horizontal positioning accuracy is improved from meter level to decimeter level.

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MP mitigation in GNSS positioning by GRU NNs and adaptive wavelet filtering

Cited by 6 publications

References 21 publications

HDDM Hardware Evaluation for Robust Interference Mitigation

HDDM Hardware Evaluation for Robust Interference Mitigation

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

Improving GNSS positioning performance of Android smart devices by a novel pseudorange correction method

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