Hybrid TOA-AOA WLS Estimator for Aircraft Network Decentralized Cooperative Localization

Liu, Yiming; Wang, Yongqing; Shen, Yuyao; Shi, Xuesen

doi:10.1109/tvt.2023.3252620

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…In order to avoid the computational bottlenecks related to centralized algorithms, distributed or decentralized methods have been investigated [7][8][9][10]. These methods [11][12][13][14] have shown to be effective and efficient at the cost of accuracy. Centralized−decentralized techniques have shown great promise in improving localization with no knowledge of the environment [1,15].…”

Section: Related Workmentioning

confidence: 99%

Multi-Vehicle Navigation Using Cooperative Localization

Oliveros,

Ashrafiuon

2023

Electronics

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This paper assesses the effectiveness of cooperative localization for improving the performance of closed-loop control systems for networks for autonomous multi-vehicle navigation. Nonlinear dynamic models of two- and three-dimensional vehicles are presented along with their linearized forms. A nonlinear control algorithm is then presented based on the dynamic model. Relative position measurement equations and their linearized forms are introduced. The state and measurement equations are then employed for the propagation and update steps of an EKF-based cooperative localization algorithm. Initially, a series of experiments with networks of quadcopters and mobile robots are presented to validate the performance of cooperative localization for state estimation with the continuous or intermittent presence of absolute measurements or their complete absence. Finally, the performance of the control algorithm is evaluated with and without cooperative localization to demonstrate its effectiveness for improving performance.

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Section: Related Workmentioning

confidence: 99%

Multi-Vehicle Navigation Using Cooperative Localization

Oliveros,

Ashrafiuon

2023

Electronics

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“…Hybrid time-of-arrival (TOA) and angle-of-arrival (AOA) localization is commonly used in wireless sensor networks (WSN) due to its high accuracy. Conventional hybrid TOA/AOA algorithms require both azimuth and zenith angle estimations at each agent, especially when the agents move in a three-dimensional (3D) space [1]. It is shown in [2], [3] that shadowing will greatly reduce TOA and AOA estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

Complexity Reduction for Hybrid TOA/AOA Localization in UAV-Assisted WSNs

Tran,

Le,

Huang

et al. 2023

IEEE Sens. Lett.

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Unmanned aerial vehicles (UAVs)-assisted wireless sensor networks (WSNs) have tremendous potential applications due to their flexibility and rapid deployment. Hybrid time-of-arrival (TOA) and angle-of-arrival (AOA) localization techniques are commonly used due to their high accuracy. Conventional TOA/AOA localization algorithms require both zenith and azimuth angle estimations at each agent. Since a zenith-and-azimuth AOA estimation requires an L-shape antenna array and complicated two-dimensional signal processing, conventional TOA/AOA algorithms lead to both hardware and computational complexity and high power consumption at each agent. This paper proposes a hybrid TOA/AOA localization algorithm, named 𝑇1𝐴 𝑎 , to reduce the agents' complexity. 𝑇1𝐴 𝑎 only combines TOA-ranging with the azimuth angle estimation. Thereby, agents only require a one-dimensional antenna array, less complicated signal processing, and thus lower power consumption. Such improvements are important for power-limited WSNs and Internetof-Things (IoT) systems. Simulations are conducted to prove that the proposed 𝑇1𝐴 𝑎 technique can achieve similar performance as conventional TOA/AOA methods, while significantly simplifying agents' complexity.

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