• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.2
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• pp.33-39
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• 2013

Multilateration(MLAT) may complement secondary surveillance radar and also act as a real-time backup for the ADS-B system. This System is using time difference of arrival (TDOA) and based on triangulation principle. Each TDOA measurement defines a hyperbola describing possible aircraft locations. The accuracy in MLAT system depends on the positional relationship of the receiver and aircraft. There are various algorithms to localize aircraft based on TOA estimation. In this paper, we use least square method and extended Kalman filter and compare their results. Study results show that the extend Kalman filter provides a better performance than the least square method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11C
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• pp.702-711
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• 2011

In this paper, we derived a closed-form equation of a Best Linear Unbiased Estimator (BLUE) and its Crammer-Rao Lower Bound (CRLB) for the estimation of the position of the emitter based on the Time Difference of Arrival (TDOA) teclmique. The BLUE and CRLB were derived for the case of estimating 2 dimensional position of the emitter with 3 base stations or sensors, and for this purpose, we nsed an approximated equation of the TDOA hyperbola equation obtained from the first order Taylor-series after setting the reference points of the position. The derived equation can be used for any kind of noises which are uncorrelated in each other in the TOA measurement noises and for a white Gaussian noise also.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.912-920
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• 2012

In this paper, we derived a closed-form equation of a Best Linear Unbiased Estimator (BLUE) estimator for the 3 dimensional estimation of the position of the emitter based on the Time Difference of Arrival (TDOA) technique. The BLUE derived for the case of estimating 3 dimensional position of the emitter with 4 base stations or sensors, and for this purpose, we used an approximated equation of the TDOA hyperbola equation obtained from the first order Taylor-series after setting the reference points of the position. The derived equation can be used for any kind of noises which are uncorrelated in each other in the TOA measurement noises and for a white Gaussian noise also.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.373-378
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• 2014

The technology of direction finding is very important to make high position fixing accuracy. TDOA(time difference of arrival) direction finding technology is a high accuracy technology and is used in RF system from 1990. The principle of TDOA is to receive an emitter signal with two antennas, measure the time difference of received signal and then convert the time differences to azimuth angle. For high DF(direction finding) accuracy long basis line and high SNR at receiving system are needed. The DF accuracy and position fixing accuracy are simulated with different SNRs and antenna base lines. We obtain the DF accuracy of $0.51^{\circ}$ at $0^{\circ}$ incident azimuth angle in case of 50m base line and 40dB SNR.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.319-324
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• 2022

If radio interference occurs or there is no navigation device, radio navigation of high-speed moving object becomes impossible. Nevertheless, if there are multiple ground stations and precise range measurement between the high-speed moving object and the ground station can be secured, it is possible to estimate the position of moving object. This paper proposes a position estimation method using high-precision TDOA measurement generated using TLM signal. In the proposed method, a common error of moving object is removed using the TDOA measurements. The measurements is generated based on TLM signal including SOQPSK PN symbol capable of precise timing synchronization. Therefore, since precise timing synchronization of the system has been performed, the timing error between ground stations has a very small value. This improved the position estimation performance by increasing the accuracy of the measured values. The proposed method is verified through software-based simulation, and the performance of estimated position satisfies the target performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.76-84
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• 2013

In the passive emitter localization using instantaneous TDOA (time difference of arrival) and FDOA (frequency difference of arrival) measurements, the estimation accuracy can be improved by collecting additional measurements. To achieve this goal, it is required to increase the number of the sensors. However, in electronic warfare environment, a large number of sensors cause the loss of military strength due to high probability of intercept. Also, the additional processes should be considered such as the data link and the clock synchronization between the sensors. Hence, in this paper, the passive localization of a stationary emitter is presented by using the successive TDOA and FDOA measurements from two moving sensors. In this case, since an independent pair of sensors is added in the data set at every instant of measurement, each pair of sensors does not share the common reference sensor. Therefore, the QCLS (quadratic correction least squares) methods cannot be applied, in which all pairs of sensor should include the common reference sensor. For this reason, a Gauss-Newton algorithm is adopted to solve the non-linear least square problem. In addition, to show the performance of the proposed method, we compare the RMSE (root mean square error) of the estimates with CRLB (Cramer-Rao lower bound) and derived the CEP (circular error probable) planes to analyze the expected estimation performance on the 2-dimensional space.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.1
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• pp.51-59
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• 2013

This paper researches location estimating method in CDMA system. Previously proposed positioning algorithms are difficult to estimate accurate position in indoor environments, and possible to limited position. This paper proposes enhanced algorithm using received PN pilot signals from base stations to enhance previous algorithms. For estimating position, we set the threshold value and use over the threshold value in received signals. After selecting signals, we estimate position using TDOA algorithm. And the cases which TDOA algorithm cannot use to estimate position, we use Pattern Matching algorithm. The proposed method system showed the improved performance in estimating parameters and locating positions by computer simulations.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.102-105
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• 2000

This paper propose new sound localization algorithm that calculates TDOA(Time Difference Of Arrival) between the two received signals via two microphone array, The proposed Subband CPSP is a development of Previous CPSP method using subband approach. It first split the received microphone signals into three frequency bands and then calculates subband CPSP with corresponding SNR weights. This type of algorithm, Subband CPSP, can provide more accurate TDOA estimation results because it limits the effects of environmental noise within each subband. To verify the performance of the proposed Subband CPSP algorithm, computer simulation was conducted and it was compared with previous CPSP method. From the both simulation results, the proposed Subband CPSP is superior to previous CPSP algorithm more than accuracy for TDOA estimation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.158-163
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• 2010

In this paper, we propose the location measurement algorithm of unknown tag based on RFID (Radio-Frequency IDentification) by using RSSI (Received Signal Strength Indication) and TDOA (Time Difference of Arrival) and extended Kalman filter in smart space. To do this, first, we recognize the location of unknown tag by using the RSSI and TDOA recognition methods. Second, we set the coordinate of the tag location measured by using trilateration and SX algorithm. But the tag location data measured by this method are included complex environmental error. So, we use the extended Kalman filter in order to revise error data of the tag location. Finally, we validate the applicability of the proposed method though the simulation in a complex environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.62-71
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• 2013

The passive emitter location method using TDOA and FDOA measurements has higher accuracy comparing to the single TDOA or FDOA based method. Moreover, it is able to estimate the velocity vector of a moving platform. Recently, several non-iterative methods were suggested using the nuisance parameter but the common reference sensor is needed for each pair of sensors. They show also relatively low performance in the case of a long range between the sensor groups and the emitter. To solve this, we derive the estimation method of the position and velocity of a moving platform based on the Gauss-Newton method. In addition, to analyze the estimation performance of the position and velocity, respectively, we decompose the CRLB matrix into each subspace. Simulation results show the estimation performance of the derived method and the CEP planes according to the given geometry of the sensors.