DNN-Aided Distributed Direct Position Determination for UAV Cluster

Lv, Liujie; Wu, Sheng; Li, Haihan; Jiang, Chunxiao; Su, Yi

doi:10.1109/tvt.2023.3295411

IEEE Trans. Veh. Technol.

2023

DOI: 10.1109/tvt.2023.3295411

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DNN-Aided Distributed Direct Position Determination for UAV Cluster

Liujie Lv

Sheng Wu

Haihan Li

et al.

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2024

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Cited by 2 publications

References 19 publications

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TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

Tausiesakul,

Asavaskulkiet

2024

IEEE Access

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An important service in the wireless systems for the human daily life is the information of a mobile user location. Wireless sensor network is a structure that can be used to determine the mobile user position. The time-difference-of-arrival (TDoA) technique is often considered for wireless localization due to the low cost of sensor network. In this work, the error covariance matrices are derived for predicting the error performance of the conventional closed-form constrained total least squares (CTLS) estimator. More importantly, three new Newton's methods are proposed for computing the CTLS solution in the TDoA localization. In addition, theoretical performance of both new Newton-based approaches is provided in closed forms. Numerical simulation is conducted to compare the derived theoretical prediction with the corresponding actual estimation error. It is illustrated that the two new Newton-based techniques provide better performance, in terms of lower bias and root mean square error, less computational time, and more reliability, than the former Newton-based algorithms. Furthermore, the derived expressions for the theoretical error covariance well coincide with the actual random estimation results.INDEX TERMS First-order Taylor's series expansion, error covariance, localization, time difference of arrival, Newton's method.

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TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

Tausiesakul,

Asavaskulkiet

2024

IEEE Access

View full text Add to dashboard Cite

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An Enhanced Direct Position Determination of Mixed Circular and Non-Circular Sources Using Moving Virtual Interpolation Array

Wang,

Zhang,

Guo

et al. 2024

Sensors

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In this study, a moving single-station direct position determination (DPD) algorithm based on virtual interpolated arrays is proposed. Existing moving single-station algorithms face challenges such as the incomplete utilization of sparse array apertures and insufficient consideration of mixed circular and non-circular signals. To address these issues, we propose an enhanced gridless DPD algorithm, suitable for multiple mixed circular and non-circular sources. Through constructing a non-zero unconjugated covariance matrix from the non-circular components of the mixed signals, the data dimensionality is expanded, and the gridless method is used to fill the voids in the coarray, significantly improving localization performance. Additionally, a unitary transformation method is applied to reduce computational complexity. This method transforms complex operations into real operations by applying unitary transformations to steering vectors and subspaces. Simulation results demonstrate that the proposed algorithm offers significant advantages in terms of array degrees of freedom and localization accuracy.

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DNN-Aided Distributed Direct Position Determination for UAV Cluster

Cited by 2 publications

References 19 publications

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

An Enhanced Direct Position Determination of Mixed Circular and Non-Circular Sources Using Moving Virtual Interpolation Array

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