Cooperative Localization With the Fusion of GNSS and Relative Range Information in Vehicular Ad-Hoc Networks

Qu, Xiaomei; Liu, Tao; Li, Fan; Tan, Wenrong

doi:10.1109/tits.2023.3287209

Cited by 8 publications

(3 citation statements)

References 42 publications

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“…There is a significant amount of research on the cooperative localization problem. One strategy is based on non-Bayesian estimation [11][12][13]. It treats the location information of UAVs as unknown deterministic parameters, which reduces localization accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…For example, time-of-arrival cooperative localization (TOA-CL) [11] roughly linearizes a nonlinear measurement function so that there is room for improvement in estimation accuracy. The maximum likelihood and iterative localization algorithm (ML-ILA) [12] integrates GNSS and relative distance information, following the ML strategy to solve a quadratic non-convex programming problem. Although positioning accuracy has been dramatically improved, it does not consider communication costs and only considers static scenarios, and the algorithm's scalability needs further research.…”

Section: Introductionmentioning

confidence: 99%

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Multi-UAV Cooperative Localization Using Adaptive Wasserstein Filter with Distance-Constrained Bare Bones Self-Recovery Particles

Xin,

Pan,

Wang

et al. 2024

Drones

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Aiming at the cooperative localization problem for the dynamic UAV swarm in an anchor-limited environment, an adaptive Wasserstein filter (AWF) with distance-constrained bare bones self-recovery particles (CBBP) is proposed. Firstly, to suppress the cumulative error from the inertial navigation system (INS), a position-prediction strategy based on transition particles is designed instead of using inertial measurements directly, which ensures that the generated prior particles can better cover the ground truth and provide the uncertainties of nonlinear estimation. Then, to effectively quantify the difference between the observed and the prior data, the Wasserstein measure based on slice segmentation is introduced to update the posterior weights of the particles, which makes the proposed algorithm robust against distance-measurement noise variance under the strongly nonlinear model. In addition, to solve the problem of particle impoverishment caused by traditional resampling, a diversity threshold based on Gini purity is designed, and a fast bare bones particle self-recovery algorithm with distance constraint is proposed to guide the outlier particles to the high-likelihood region, which effectively improves the accuracy and stability of the estimation. Finally, the simulation results show that the proposed algorithm is robust against cumulative error in an anchor-limited environment and achieves more competitive accuracy with fewer particles.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-UAV Cooperative Localization Using Adaptive Wasserstein Filter with Distance-Constrained Bare Bones Self-Recovery Particles

Xin,

Pan,

Wang

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

“…A variety of range-based CP methods have been proposed in the latest literatures [21][22][23][24][25]. Most of these works assume that the inter-node ranging is always available and accurate enough.…”

Section: Introductionmentioning

confidence: 99%

Factor Graph Weight Particles aided Distributed Underwater Cooperative Positioning Algorithm

zhang

Tang

et al. 2021

Preprint

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The growing scale of marine exploration requires high-resolution underwater localization, which necessitates cooperation among underwater network nodes, considering the channel complexity and power efficiency. In this paper, we proposed factor graph weight particles aided distributed underwater nodes cooperative positioning algorithm (WP-DUCP). It capitalized on the factor graph and sum-product algorithm to decompose the global optimization to the product of several local optimization functions. Combined with the Gaussian parameters to construct the weighted particles and to realize the belief transfer, it shows low complexity and high efficiency, suitable to the energy-restricted and communication distance-limited underwater networks. In terms of convergence, localization resolution, and computation complexity, we conducted the simulation and real-test with comparison to the existing co-localization methods. The results verified a higher resolution of the proposed method with no extra computation burden.

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Drones for automated parcel delivery: Use case identification and derivation of technical requirements

Zieher,

Olcay,

Kefferpütz

et al. 2024

Transportation Research Interdisciplinary Perspectives

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Cooperative Localization With the Fusion of GNSS and Relative Range Information in Vehicular Ad-Hoc Networks

Cited by 8 publications

References 42 publications

Multi-UAV Cooperative Localization Using Adaptive Wasserstein Filter with Distance-Constrained Bare Bones Self-Recovery Particles

Multi-UAV Cooperative Localization Using Adaptive Wasserstein Filter with Distance-Constrained Bare Bones Self-Recovery Particles

Factor Graph Weight Particles aided Distributed Underwater Cooperative Positioning Algorithm

Drones for automated parcel delivery: Use case identification and derivation of technical requirements

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