• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1080-1084
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• 2007

Many different methods for sound source localization have been developed. Most of them mainly depend on time delay of arrival (TDOA) or on empirical or analytic head related transfer functions (HRTFs). In real implementation, since the direct path between a source and a sensor is interrupted by obstacles as like a head or body of robot, it has to be considered the number of sensors as well as their positions. Therefore, in this paper, we present the methods, which are included sensor position problem, to localize the sound source with 4 microphones to cover the 3D space. Those are modified two-step TDOA methods. Our conclusion is that the different method has to be applied in case to be different microphone position on real robot platform.

• 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 the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.85-91
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• 2013

For location based service and context awareness services, accurate indoor positioning technology is essential. The TDOA method that uses the range difference between signal source and receivers for estimating the location of the signal source, has estimation error due to measurement error. In this paper, a new algorithm is proposed to select the real root among calculated roots using the range difference information, and the estimated position of the signal source shows good accuracy compared to the existing method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.3
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• pp.244-250
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• 2018

Multilateration acquires the transponder signal of target from receivers installed on the ground and calculates the position of the target using the difference of the signal acquisition time of each receiver. One of the factors that influence the positioning accuracy of Multilateration using the TDOA calculation method is the error due to the precision measurement of signal input time. When measuring the signal input time at the receiver, the input signal is sampled using the reference clock of the receiver and a reference sample having the same sampling rate is applied to the cross correlation technique. Therefore, the accuracy of the signal input time is proportional to the reference clock. In this paper, the algorithm for precisely measuring the signal input time by performing cross correlation between the input signal of the receiver and DRS(Delayed Reference Sample) is proposed. In order to verify this, we implemented the pulse signal of the transponder that is transmitted from the target using Matlab. Through the simulation, cross correlation between the proposed DRS and the input signal was performed. From this result, the performance of the precise measurement of signal input time was analyzed.

• 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.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1800_1801
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• 2009

본 논문에서는 실내 환경에서 신호세기를 이용한 RSSI(Received Signal Strength Indication)인식 방법과 신호의 도착 시간 차이를 이용한 TDOA(Time Difference Of Arrival )인식 방법을 이용하여 태그 위치 측정 및 오차 보정 방법을 제안한다. 제안한 방법은 물체 위치 인식을 위해 기존의 제안된 거리에 따라 발생하는 경로손실(Path Loss) 방정식과 신호의 도착 시간차이를 이용하여 태그를 인식한 다음 삼각측량법과 SX 알고리즘을 이용하여 태그의 위치를 측정한다. 또한, 실내 환경의 다양한 오차를 포함하고 있는 태그의 위치 측정 데이터에 대해 확장된 칼만 필터를 사용하여 오차를 보정하는 방법을 제안한다. 마지막으로 몇 개의 시뮬레이션을 통하여 그 응용 가능성을 증명한다.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.117-119
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• 2014

In this paper, we shows the simulation result of estimation algorithm for aircraft track which is core engine in MLAT system. The simulation result for 3D position estimation by Chan algorithm based on TDOA and Kalman filter shows that the performance satisfies the requirements of EUROCAE ED-117 over AWGN channel.

• 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.

• Korean Management Science Review
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• v.29 no.3
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• pp.1-11
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• 2012

This paper considers a localization problem in time difference of arrival (TDOA)-based radio frequency identification (RFID) systems. To estimate the position of a target tag, this paper suggests three localization algorithms that use benchmark tags. The benchmark tags are the same type as the target tag, but either the locations or distance of the benchmark tags are known. Two algorithms use the benchmarks for auxiliary information to improve the estimation accuracy of the other localization algorithms such as least squared estimator (LSE). The other one utilizes the benchmarks as essential tags to estimate the location. Numerical tests show that the localization accuracy can be improved by using benchmark tags especially when an algorithm using the LSE is applied to the localization problem. Furthermore, this paper shows that our benchmark algorithm is valuable when the measurement noise is large.