Tensor-Based Framework With Model Order Selection and High Accuracy Factor Decomposition for Time-Delay Estimation in Dynamic Multipath Scenarios

Zanatta, Mateus da Rosa; Costa, João Paulo; Antreich, Felix; Haardt, Martin; Elger, Gordon; Mendonça, Fábio Lúcio Lópes de; Sousa, Rafael T. de

doi:10.1109/access.2020.3024597

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…The CDMA signals are sensitive to the non-line-of-sight (NLOS) ray within one chip range, causing big issues in channel estimation. In recent years, super-resolution algorithms (SRAs) emerged in GNSS signal processing to separate line-of-sight (LOS) and NLOS signals into different orthogonal spaces [6][7][8]. Recent work presented a graph Fourier transform (GFT) filter denoising the complex correlator outputs to replace the old GNSS tracking loop, which can be considered a direct way to steer the code phase in challenging cases [9].…”

Section: Introductionmentioning

confidence: 99%

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

et al. 2023

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Many multi-sensor navigation systems urgently demand accurate positioning initialization from global navigation satellite systems (GNSSs) in challenging static scenarios. However, ground blockages against line-of-sight (LOS) signal reception make it difficult for GNSS users. Steering local codes in GNSS basebands is a desirable way to correct instantaneous signal phase misalignment, efficiently gathering useful signal power and increasing positioning accuracy. Inertial navigation systems (INSs) have been used as effective complementary dead reckoning (DR) sensors for GNSS receivers in kinematic scenarios, resisting various forms of interference. However, little work has focused on whether INSs can improve GNSS receivers in static scenarios. Thus, this paper proposes an enhanced navigation system deeply integrated with low-cost INS solutions and GNSS high-accuracy carrier-based positioning. First, an absolute code phase is predicted from base station information and integrated solutions of the INS DR and real-time kinematic (RTK) results through an extended Kalman filter (EKF). Then, a numerically controlled oscillator (NCO) leverages the predicted code phase to improve the alignment between instantaneous local code phases and received ones. The proposed algorithm is realized in a vector-tracking GNSS software-defined radio (SDR). Results of the time-of-arrival (TOA) and positioning based on real-world experiments demonstrated the proposed SDR.

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Section: Introductionmentioning

confidence: 99%

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

et al. 2023

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“…The authors of [35] developed a Structured CP Decomposition (SCPD) based channel estimation algorithm, which leveraged the fact that the channel can be represented as a low-rank higher-order tensor. It was also adopted to estimate the sparse channel parameters in [36]. The method, however, does not fully exploit multiple RF chains and requires that the channel must be fixed during the estimation process that takes many subframes/frames in the time domain.…”

Section: Introductionmentioning

confidence: 99%

Sparse Bayes Tensor and DOA Tracking Inspired Channel Estimation for V2X Millimeter Wave Massive MIMO System

Luo

Zhou

Wang

et al. 2021

Sensors

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Efficient vehicle-to-everything (V2X) communications improve traffic safety, enable autonomous driving, and help to reduce environmental impacts. To achieve these objectives, accurate channel estimation in highly mobile scenarios becomes necessary. However, in the V2X millimeter-wave massive MIMO system, the high mobility of vehicles leads to the rapid time-varying of the wireless channel and results in the existing static channel estimation algorithms no longer applicable. In this paper, we propose a sparse Bayes tensor and DOA tracking inspired channel estimation for V2X millimeter wave massive MIMO system. Specifically, by exploiting the sparse scattering characteristics of the channel, we transform the channel estimation into a sparse recovery problem. In order to reduce the influence of quantization errors, both the receiving and transmitting angle grids should have super-resolution. We obtain the measurement matrix to increase the resolution of the redundant dictionary. Furthermore, we take the low-rank characteristics of the received signals into consideration rather than singly using the traditional sparse prior. Motivated by the sparse Bayes tensor, a direction of arrival (DOA) tracking method is developed to acquire the DOA at the next moment, which equals the sum of the DOA at the previous moment and the offset. The obtained DOA is expected to provide a significant angle information update for tracking fast time-varying vehicular channels. The proposed approach is evaluated over the different speeds of the vehicle scenarios and compared to the other methods. Simulation results validated the theoretical analysis and demonstrate that the proposed solution outperforms a number of state-of-the-art researches.

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GNSS User Technology: State-of-the-Art and Future Trends

Egea-Roca¹,

Arizabaleta-Diez²,

Pany³

et al. 2022

IEEE Access

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Advances in the miniaturization, computational capabilities, and cost reduction of semiconductor technology have made global navigation satellite systems (GNSSs) the favorite choice for positioning. Currently, positioning is a key factor for many essential tasks in our modern society and will become even more important with the advent of new concepts such as the Internet of Things (IoT), smart cities and autonomous driving. The extensive use of GNSSs in a wide range of applications has caused their migration from the professional segment to the mass-market segment in terms of both technology and performance. This presents new and more stringent requirements in terms of accuracy, robustness, ubiquity, and continuity for the original "open sky" GNSS design. GNSS technology has experienced an unprecedented evolution in the last decade, and it is expected to exponentially evolve in the next decade. This evolution is considered in this paper with the aim of providing a unified reference for current GNSS receiver technologies and solutions and its expected evolution in the next decade. We consider receiver concepts, antennae, RF front ends, digital signal processing, and positioning algorithms. The impacts on the different GNSS market segments and applications are also analyzed.

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Tensor-Based Framework With Model Order Selection and High Accuracy Factor Decomposition for Time-Delay Estimation in Dynamic Multipath Scenarios

Cited by 4 publications

References 32 publications

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

Sparse Bayes Tensor and DOA Tracking Inspired Channel Estimation for V2X Millimeter Wave Massive MIMO System

GNSS User Technology: State-of-the-Art and Future Trends

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