Accuracy comparison of time difference of arrival based source localization methods

Cakir, Oguzhan; Yazgan, Ayhan; Kaya,

doi:10.1109/tsp.2015.7296462

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…The calculations are proposed by using a linear least square (LLS) problem for the TDOA solution, as representative for a conservative estimation of the performance of each analyzed network. Indeed, not only has LLS been shown to reach poorer performance, when compared to other, iterative, methods [14,31], but the implementation of a simple method needing low calculus power is perfectly representative with the future perspective of implementing low-cost SDR-based networks, as already presented in this paragraph. The estimation of MDOP has thus to be considered a worst case estimation of the potential positioning accuracy of the analyzed network.…”

Section: Introductionmentioning

confidence: 84%

“…A LLS method is selected as representative for a worst case estimation of the positioning accuracy. Indeed, the method introduces an inherent approximation of the TDOA solution, which is found through the solution of a linear system, and it has been demonstrated as the least precise method for TDOA positioning [31]. This method is implemented to provide a conservative estimation of the network accuracy.…”

Section: Linear Least Squares (Lls) Methods For Tdoa Positioningmentioning

confidence: 99%

“…The estimation of MDOP has thus to be considered a worst case estimation of the potential positioning accuracy of the analyzed network. Improvements on the performance, with respect to what is presented with the MDOP, can be introduced by adopting a more precise hyperbolic navigation solution method (such as in [29,31,32]), or by improving the accuracy of the sensors. While the MDOP description gives an estimation of the worst case precision of the network, the maximum achievable accuracy can be deduced through the Cramer−Rao Lower Bound [31,32].…”

Section: Introductionmentioning

confidence: 99%

“…Improvements on the performance, with respect to what is presented with the MDOP, can be introduced by adopting a more precise hyperbolic navigation solution method (such as in [29,31,32]), or by improving the accuracy of the sensors. While the MDOP description gives an estimation of the worst case precision of the network, the maximum achievable accuracy can be deduced through the Cramer−Rao Lower Bound [31,32]. At the end of the paper, performance maps will be shown for the most convenient configuration, in order to show indicative values of DOP, given the baseline and station number, and indicative plots of the needed time precision for the single sensors, when assigning a given position determination value.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Time Difference of Arrival (TDOA) Networks Performance for Launcher Vehicles and Spacecraft Tracking

2020

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Time Difference of Arrival (TDOA) networks could support spacecraft orbit determination or near-space (launcher and suborbital) vehicle tracking for an increased number of satellite launches and space missions in the near future. The evaluation of the geometry of TDOA networks could involve the dilution of precision (DOP), but this parameter is related to a single position of the target, while the positioning accuracy of the network with targets in the whole celestial vault should be evaluated. The paper presents the derivation of the MDOP (minimum dilution of precision), a parameter that can be used for evaluating the performance of TDOA networks for spacecraft tracking and orbit determination. The MDOP trend with respect to distance, number of stations and target altitude is reported in the paper, as well as examples of applications for network performance evaluation or time precision requirement definitions. The results show how an increase in the baseline enables the inclusion of more impactive improvements on the MDOP and the mean error than an increase in the number of stations. The target altitude is demonstrated as noninfluential for the MDOP trend, making the networks uniformly applicable to lower altitude (launchers and suborbital vehicles) and higher altitude (Low and Medium Earth Orbits satellites) spacecraft.

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Section: Introductionmentioning

confidence: 84%

Section: Linear Least Squares (Lls) Methods For Tdoa Positioningmentioning

confidence: 99%