Polynomial Fitting and Interpolation Method in TDOA Estimation of Sensors Network

Yang, Jianhui; Yan, Tianfeng; Sun, Wenhao

doi:10.1109/jsen.2022.3232625

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…The gradient in (54) and the Hessian in (55) appear to be complicated, leading to computational demanding. In what follows, we derive a new simpler expression of both quantities.…”

Section: B Constrained Total Least Squares Using Newton's Methods Wit...mentioning

confidence: 99%

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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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“…The gradient in (54) and the Hessian in (55) appear to be complicated, leading to computational demanding. In what follows, we derive a new simpler expression of both quantities.…”

Section: B Constrained Total Least Squares Using Newton's Methods Wit...mentioning

confidence: 99%

“…The NM is adopted in [47] for the TDOA localization. This work is also considered in [54]- [56]. The disadvantage of the NM in [47] is that the gradient and Hessian involve cumbersome expressions.…”

Section: Introductionmentioning

confidence: 99%