An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

Luo, Zhibin; Ding, Jianguo; Zhao, Lin; Wu, Mouyan

doi:10.3390/s17112668

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…In recent years, Tang, Wu, Luo, Yang, et al, have attempted to employ Kalman filtering on the output values of the code and carrier ring discriminators. This approach aims to enhance the tracking capability of the VT for satellite signals and subsequently improve the positioning stability and accuracy of GNSS receivers [9,24,26,27,42].…”

Section: Fundamentals Of Vtmentioning

confidence: 99%

“…In the MEEKF-based loop filter, the output code phase error ∆τ of the code discriminator, carrier phase error ∆ φ , and carrier frequency error ∆ f of the carrier discriminator were selected as the measurement vector [26]: The measurement transition matrix can be expressed directly as:…”

Section: Vtl Design Based On Meementioning

confidence: 99%

“…Luo et al conducted an extensive analysis of both coherent and non-coherent integrations and proposed an enhanced design for the non-coherent pre-filter. The objective was to improve the accuracy in estimating the carrier phase error, carrier frequency error, and code phase error [26]. Yang et al proposed a cascaded adaptive VT method that is based on the KF + EKF architecture.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Liu,

Chen,

et al. 2024

Meas. Sci. Technol.

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In recent years, Unmanned Surface Vehicles (USVs) have increasingly been used for river monitoring and hydrological surveys. USVs rely on global navigation satellite systems (GNSS) for navigation. However, signal blocking can cause the traditional GNSS vector tracking loop to increase the code phase and carrier frequency errors, leading to higher positioning errors that do not meet USVs’ requirements. To address this problem, we propose a vector tracking method based on the minimum error entropy (MEE) in the signal tracking module. The minimum error entropy Kalman filter (MEEKF) is adopted as the loop filter to mitigate code phase and carrier frequency errors, reduce non-Gaussian noise and random errors generated by signal blocking, and enhance the positioning accuracy and robustness of USV navigation. The measurement noise covariance of the loop filter was adjusted adaptively using the signal carrier-to-noise ratio (CNR). A field experiment was conducted using a commercial GNSS receiver as reference. The results demonstrate a 19.3% improvement in positioning accuracy compared with the traditional method in an open environment. Moreover, the proposed method maintains stable operation and achieves a 79.4% improvement in positioning accuracy during signal blocking. This novel algorithm offers a new concept for USV navigation systems to cope with signal blocking.

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Section: Fundamentals Of Vtmentioning

confidence: 99%

Section: Vtl Design Based On Meementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Liu,

Chen,

et al. 2024

Meas. Sci. Technol.

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“…The direction of a dynamic object can be computed by the function atan2 that provides the angular difference between the two points [44]. Then, an angular deviation of 180 degrees is added to this difference, generating the course of the dynamic object.…”

Section: Semantic Description and Dynamic Interaction (Sd2i)mentioning

confidence: 99%

Intelligent 3D Perception System for Semantic Description and Dynamic Interaction

Teixeira

Nogueira

Dalmedico

et al. 2019

Sensors

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This work proposes a novel semantic perception system based on computer vision and machine learning techniques. The main goal is to identify objects in the environment and extract their characteristics, allowing a dynamic interaction with the environment. The system is composed of a GPU processing source and a 3D vision sensor that provides RGB image and PointCloud data. The perception system is structured in three steps: Lexical Analysis, Syntax Analysis and finally an Analysis of Anticipation. The Lexical Analysis detects the actual position of the objects (or tokens) in the environment, through the combination of RGB image and PointCloud, surveying their characteristics. All information extracted from the tokens will be used to retrieve relevant features such as object velocity, acceleration and direction during the Syntax Analysis step. The anticipation step predicts future behaviors for these dynamic objects, promoting an interaction with them in terms of collisions, pull, and push actions. As a result, the proposed perception source can assign relevant information to mobile robots, not only about distances as traditional sensors, but about other environment characteristics and object behaviors. This novel perception source introduces a new class of skills to mobile robots. Experimental results obtained with a real robot are presented, showing the proposed perception source efficacy and potential.

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“…[2] proposes an FFT discrimination method with a wider pull-in range, which utilizes an abnormal value elimination method to eliminate the discriminated results that can differ greatly from the actual values. [3] introduces a simple fault detection and exclusion (FDE) structure, which extends the effective working range of the estimated carrier phase error but its working range is still limited. When employing the maximum likelihood estimation (MLE) method to estimate the frequency, not only the frequency estimation range can be set as needed, but also the Cramer-Rao Lower Bound (CRLB) of the estimated error variance can be achieved [4].…”

Section: Introductionmentioning

confidence: 99%

Optimized carrier tracking loop design for high dynamic and low CNR conditions

ji,

lin,

liang

2023

Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023)

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The carrier tracking loop face extreme difficulty in entering a locked-in state for high dynamic and low carrier-to-noise ratio (CNR) environment. To address this issue, this paper presents an improved Frequency-Locked Loop (FLL) serially assisted Phase-Locked Loop (PLL). The improved carrier tracking loop design consists of a high-dynamic frequency discriminator and a high-dynamic loop filter based on second-order FLL serially assisted third-order PLL. In particular, this proposed frequency discriminator executes an adaptive switching mechanism between the maximum likelihood estimation (MLE) discriminator and the conventional frequency discriminator. Once the Doppler frequency estimation error begins to accumulate, the MLE discriminator will be selected which can pull the Doppler frequency into the working range of the conventional frequency discriminator. Thus, a wider pull-in range can be obtained to provide good frequency discrimination capabilities under high dynamic conditions. The experimental results and comparative analysis demonstrate that the improved FLL serially assisted PLL can achieve an improved tracking performance under high dynamic and low CNR conditions.

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An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

Cited by 10 publications

References 12 publications

Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

Intelligent 3D Perception System for Semantic Description and Dynamic Interaction

Optimized carrier tracking loop design for high dynamic and low CNR conditions

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