Derivation of an Approximate Location Estimate in Angle-of-Arrival Based Localization in the Presence of Angle-of-Arrival Estimate Error and Sensor Location Error

An, Do-Jin; Lee, Joon-Ho

doi:10.1109/wsce.2018.8690530

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Traditional radar positioning networks typically include two types of nodes: anchors with known positions and radars with unknown positions. The positions of radars are determined through measurements from other active radars and anchors, including time of arrival (TOA) [3,4], time difference of arrival (TDOA) [5,6], angle of arrival (AOA) [7,8], received signal strength (RSS) [9,10], and so on. In addition to active positioning, this paper also conducts research on passive sensing, where positions of the targets can be determined through time sum of arrival (TSOA) [11,12].…”

Section: Introduction 1background and Motivationmentioning

confidence: 99%

Resource Optimization Using a Step-by-Step Scheme in Wireless UWB Sensing and Localization Networks

Zhang,

Yang,

Jia

et al. 2024

Applied Sciences

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Wireless localization and target sensing both rely on precise extraction of parameters such as signal amplitude, propagation delay, and Doppler shift from the received signals. Due to the high multi-path resolution and strong penetration, both localization and sensing can be achieved through identical UWB waveforms. In this paper, we try to properly allocate resources for localization and sensing to fully exploit the potential of UWB systems. Considering the complexity of the multi-slot networks, we derive the Fisher Information Matrix (FIM) expressions for single-slot and dual-slot integrated sensing and localization (ISAL) networks, respectively, and propose two resource optimization schemes, namely the step-by-stepscheme and the integrated scheme, respectively. The numerical results show that: (i) for the sensing-resource-limited networks with relatively uniform node distribution, the energy allocated to each step in the step-by-step scheme satisfies the relationship energy for clock offset < energy for radar localization < energy for target sensing; (ii) in the multi-slot ISAL networks, more energy will be allocated to the time slots where the networks are relatively sensing-resource-limited; (iii) the step-by-step scheme is more suitable for the sensing-resource-abundant networks, while the integrated scheme is more suitable for the sensing-resource-limited networks.

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Section: Introduction 1background and Motivationmentioning

confidence: 99%

Resource Optimization Using a Step-by-Step Scheme in Wireless UWB Sensing and Localization Networks

Zhang,

Yang,

Jia

et al. 2024

Applied Sciences

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“…Considering the flexibility and robustness of above‐mentioned trajectory estimation methods, the influence of angle‐of‐arrival estimation error and sensor position error on location accuracy was studied detailedly in [5 ]. In addition, in terms of mass decrease during the target flight, the influence of target mass decrease on location accuracy was analysed and the target mass model was corrected accordingly [6 ].…”

Section: Introductionmentioning

confidence: 99%

Target trajectory estimation by unambiguous phase differences from a single fixed passive sensor

et al. 2020

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In this Letter, considering the configuration of small antenna array aperture used for special usage, the authors proposed a target trajectory estimation method by unambiguous phase differences with prior knowledge on target velocity from a single fixed passive sensor. First, they developed the maximum likelihood estimator of the target trajectory parameters based on unambiguous phase differences and then deduce the corresponding Cramer-Rao lower bound. Furthermore, in terms of the error in prior knowledge on target velocity, the influence of target velocity mismatch on trajectory parameters estimation is analysed. Finally, they evaluated the performance of the proposed method and validated the correctness of their analysis via numerical simulation.

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UWB System and Algorithms for Indoor Positioning

Gao

Postolache

Yang

et al. 2021

2021 Telecoms Conference (ConfTELE)

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This research work presents of study of ultra-wide band (UWB) indoor positioning considering different type of obstacles that can affect the localization accuracy. In the actual warehouse, a variety of obstacles including metal, board, worker and other obstacles will have NLOS (non-line-of-sight) impact on the positioning of the logistics package, which influence the measurement of the distance between the logistics package and the anchor , thereby affecting positioning accuracy. A new developed method attempts to improve the accuracy of UWB indoor positioning, through and improved positioning algorithm and filtering algorithm. In this project, simulate the warehouse environment in the laboratory, several simulation proves that the used Kalman filter algorithm and Markov algorithm can effectively reduce the error of NLOS. Experimental validation is carried out considering a mobile tag mounted on a robot platform.

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Derivation of an Approximate Location Estimate in Angle-of-Arrival Based Localization in the Presence of Angle-of-Arrival Estimate Error and Sensor Location Error

Cited by 5 publications

References 4 publications

Resource Optimization Using a Step-by-Step Scheme in Wireless UWB Sensing and Localization Networks

Resource Optimization Using a Step-by-Step Scheme in Wireless UWB Sensing and Localization Networks

Target trajectory estimation by unambiguous phase differences from a single fixed passive sensor

UWB System and Algorithms for Indoor Positioning

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