Hybrid TDOA/AOA Localization Algorithm for GPS Jammers

임덕원,; 강재민,; 허문범,

doi:10.5302/j.icros.2014.13.1943

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…However, this TDOA-AOA combined algorithm requires calculating the Cramér-Rao lower bound (CRLB) and shows high complexity. Lim and Kang [14,15] proposed vertical position estimation based on AOA localization algorithm and horizontal position estimation based on TDOA localization algorithm. This method could achieve high 3D positioning accuracy but does not consider the measurement errors caused by the environment of the equipment.…”

Section: Introductionmentioning

confidence: 99%

TDOA Localization Algorithm based on Weight Fusion of Target Position Coordinates

QingYi¹,

Zhang²,

Sun³

2017

JESTR

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The use time of difference of arrival (TDOA) or angle of arrival (AOA) in locating the target requires at least four base stations. The measurement accuracy of different base stations varies due to different relative positions of the base station and the target. Therefore, the measurement results of different base stations cannot be discussed simultaneously. A new TDOA localization algorithm based on weighting fusion of position coordinates of target source was proposed to address this problem. First, maximum likelihood estimation was used to acquire the position coordinates of multiple groups of target sources on the 2D plane with time of arrival (TOA) and AOA of signals from base stations to the target source. Second, the coordinates were applied with weighted fusion according to the relative angle between the signals emitted from the base stations and target source to obtain relatively accurate 3D position coordinates. Finally, the proposed algorithm was compared with TDOA localization algorithm and TDOA-AOA combined localization algorithm. Results reveal that the proposed algorithm increases accuracy by 68.33% and 48.27% compared with TDOA localization algorithm and TDOA-AOA combined localization algorithm, respectively. Weighting data fusion can increase the calculation accuracy more effectively than the averaging method. This study increases the accuracy of 3D target localization in complicated environment. The proposed method shows prospect to optimize the wireless positioning technology in military and civilian fields.

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Section: Introductionmentioning

confidence: 99%

TDOA Localization Algorithm based on Weight Fusion of Target Position Coordinates

QingYi¹,

Zhang²,

Sun³

2017

JESTR

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“…The last type of method to handle NLOS in wireless sensor networks is the hybrid method, and it applies TDOA/AOA [17] or TOA/AOA [18] to estimate the hybrid locations. This kind of method can improve the precision of estimated locations to a certain extent, but when the error of some measured value from one method exceeds the threshold, the result is still bad.…”

Section: Paper Game Theory Based Location Smoothing In Wireless Sensomentioning

confidence: 99%

Game Theory Based Location Smoothing in Wireless Sensor Networks

Yongqiang

Qin²,

Wang³

2016

Int. J. Onl. Eng.

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Abstract-Location estimation of mobile target is an important research in wireless sensor networks. However, the phenomenon of non line of sight affects the accuracy of location estimating algorithms greatly. In order to improve the accuracy of location estimation of mobile targets, we proposed a game theory based location method algorithm in wireless sensor networks. In the proposed method, we first estimate the initial locations of mobile target with a support vector regression model, and then use game theory to smooth the already estimated locations. In the game model, game based filter and noise generator are two game rivals. The game filter aims to minimize the objective function of the game model, and the noise generator aims to maximize the same objective function. We propose a differential game theory based algorithm for solving the optimal resolution. The experiments show that, the proposed method is more powerful, and can be used to mobile target locating and tracking.

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“…So, a more active solution such as spoofer localization is required. Until now, some jammer localization methods have used time-difference-of-arrival (TDOA) and hybrid TDOA/angle-of-arrival (Lindström et al 2007, Bhatti et al 2012, Cetin et al 2014, Lim et al 2014. In these cases, array processing has been used for localizing the jamming signal source.…”

Section: Introductionmentioning

confidence: 99%

Ranging Performance for Spoofer Localization using Receiver Clock Offset

Lee¹,

Seo²,

Jee³

et al. 2016

Journal of Positioning, Navigation, and Timing

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In this paper, the performance of ranging measurement, which is generated using two receiver clock offsets in one receiver, was analyzed. A spoofer transmits a counterfeited spoofing signal which is similar to the GPS signal with hostile purposes, so the same tracking technique can be applied to the spoofing signal. The multi-correlator can generate two receiver clock offsets in one receiver. The difference between these two clock offsets consists of the path length from the spoofer to the receiver and the delay of spoofer system. Thus, in this paper, the ranging measurement was evaluated by the spoofer localization performance based on the time-of-arrival (TOA) technique. The results of simulation and real-world experiments show that the position and the system clock offset of the spoofer could be estimated successfully.

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Hybrid TDOA/AOA Localization Algorithm for GPS Jammers

Cited by 7 publications

References 10 publications

TDOA Localization Algorithm based on Weight Fusion of Target Position Coordinates

TDOA Localization Algorithm based on Weight Fusion of Target Position Coordinates

Game Theory Based Location Smoothing in Wireless Sensor Networks

Ranging Performance for Spoofer Localization using Receiver Clock Offset

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