• Journal of Communications and Networks
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• v.14 no.5
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• pp.533-539
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• 2012

The performance analysis of wireless geolocation in a non-line-of-sight (NLOS) environment is a very important issue. Since Cramer-Rao lower bound (CRLB) determines the physical impossibility of the variance of an unbiased estimator being less than the bound, many studies presented the performance analysis in terms of CRLB. Several CRLBs for time-of-arrival (TOA), pseudo-range TOA, angle-of-arrival (AOA), and signal strength (SS) based positioning methods have been derived for NLOS environment. However, the performance analysis of time difference of arrival (TDOA) and TDOA/SS based geolocation techniques in a NLOS environment is still an opening issue. This paper derives the CRLBs of TDOA and TDOA/SS based positioning methods for NLOS environment. In addition, theoretical analysis proves that the derived CRLB for TDOA is the same as that of pseudo-range TOA and the TDOA/SS scheme has a lower CRLB than the TDOA (or SS) scheme.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.394-397
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• 2001

There are several methods of measuring position. For example GPS, AOA, TDOA and using radio camera. In this Paper I used TDOA method in position measuring system. TDOA method uses arrival time difference. In position measuring system, three transfers which is placed in different position transfer signal to receiver in fixed time interval and receiver records arrival time of signal. Because receiver knows idle signal's arrival time, receiver can calculate the difference of the signal's arrival time between idle and real. When we obtain time difference we can know the receiver position by Newton Raphson method.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.105-114
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• 2015

This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.608-615
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• 2007

Generally time of arrival (TOA) information via two way communications can be derived by accurate round trip time (RTT) between two devices. However, response time demanded in RTT measurement is long, a serious TOA error is caused by each different clock drift between two devices. In order to solve this problem, we propose the TOA and time difference of arrival (TDOA) estimation scheme with mitigating clock drift effect. To verify the performance of proposed method, we compared the proposed scheme with one way based TDOA acquisition method introduced by IEEE 802.15.4a Task Group and then we could conclude that the proposed method has better performance over other methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.571-576
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• 2022

Due to the epochal development of the unmanned technology, the importance of LDT(: Location Detection Technology), which accurately estimates the location of a user or object, is dramatically increased. TOA(: Time of Arrival), which calculates a location by measuring the arrival time of signals, and TDOA(: Time Difference of Arrival) which calculates it by measuring the difference between two arrival times, are representative LDT methods. Based on the signals received from three or more base stations, TOA calculates an intersection point by drawing circles and TDOA calculates it by drawing hyperbolas. In order to improve the radio shadow area problem, a huge number of repeaters have been installed in the urban area, but the signals received through these repeaters may cause the serious error for estimating a location. In this paper, we propose an efficient location estimation technique using the signal received through the repeater. The proposed approach estimates the location of MS(: Mobile Station) employing TOA and TDOA methods, based on signals received from one repeater and two BS(: Base Station)s.

• ETRI Journal
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• v.34 no.2
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• pp.260-263
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• 2012

In this letter, we propose a moving-target tracking algorithm based on a particle filter that uses the time difference of arrival (TDOA)/frequency difference of arrival (FDOA) measurements acquired by distributed sensors. It is shown that the performance of the proposed algorithm, based on the particle filter, outperforms the one based on the extended Kalman filter. The use of both the TDOA and FDOA measurements is shown to be effective in the moving-target tracking. It is proven that the particle filter deals with the nonlinear nature of the movingtarget tracking problem successfully.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.746-756
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• 2013

The emitter geolocation method using the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) has more accurate performance comparing to the single TDOA or FDOA based method. The estimation performance varies with the sensor paring strategies, the deployment and velocities of the sensors. Therefore, to establish effective strategy on the electronic warfare system, it is required to analyze the relation between the estimation accuracy and the operational condition of sensors. However, in the conventional non-iterative method, the restriction of the deployment of sensors and the reference sensor exists. Therefore, we derive the emitter geolocation method based on a Gauss-Newton method which is available to apply to any various sensor pairs and the deployment and velocities of the sensors. In addition, simulation results are included to compare the performance of geolocation method according to the used measurements: the combined TDOA/FDOA, TDOA, and FDOA. Also, we present that the combined TDOA/FDOA method outperforms over single TDOA or FDOA on the estimation accuracy with the CEP plane.

• Journal of Advanced Navigation Technology
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• v.21 no.2
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• pp.163-170
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• 2017

MLAT which is an independent cooperative surveillance system is applied to increase the positon resoultin of secondary survelliance radar. MLAT uses the hyperboic or hyperboloid position mesurement algorithm. Central processing unit of MLAT calculates target position using time difference of arrival (TDOA) which can be solved from time of arrival (TOA) information of each receivers (at least 4 receivers). To increase position resolution of MLAT which use TDOA, TOA which is transfer time from tranmitter to receiver shold be calculated with precision time resolution in receiver. This paper explained the MLAT system briefly and explained ATD which is one of means of calcuating pulse position. ATD is applied to solve the deviation of pulse position due to different amplitude of signals in mulitiple receivers. In this paper, to analysis the performance of ATD, the simulation result of LAS and CDS was compared with the simulation result of basic threshold method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5208-5213
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• 2011

In this paper, we proposed a new direction finding(DF) technology using TDOA(time-difference of arrival) and PDOA(phase difference of arriving signal) method. The proposed technology has a good DF accuracy without DF ambiguity. TDOA or PDOA technology is used to the most of intelligence systems in 21 century. The principle of TDOA is to receive a signal with two parallel antennas, measure the time difference of arrival signal, and converse the time difference to the direction of incident signal. Those technology make a DF system small size but the DF accuracy is low into short antenna installation distance. The principle of PDOA is similar to TDOA except measuring the phase difference of arrival signal, These technology get a good DF accuracy in short antenna installation distance but have a DF ambiguity. The proposed DF method is simulated into DF system operation environment with noise, and has a good DF accuracy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.138-142
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• 2006

Time Difference of Arrival (TDOA) algorithm was applied to sound source positioning. Using measured microphones signal, difference of distance from source to sensors were estimated by TDOA and speed of sound, and taken by navigational measurements. And iteration procedures were induced to find the actual source location. For the case of stationary and moving sound source, validation test were performed in the anechoic room. In the stationary case, the error of positioning is less then 1.3% in length scale, and it could be seen proper filtering processes were required in the application of moving sound source.