• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.255-261
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• 2004

The problem of geolocation using multiple satellites is to determine the position of a transmitter located on the Earth by processing received signals. The specific problem addressed in this paper is that of estimating the position of a stationary transmitter located on or above the Earth's surface from measured time difference of arrivals (TDOA) by a geostationary orbiting (GSO) satellite and a low earth orbiting (LEO) satellite. The proposed geolocation method is based on the total least squares (TLS) algorithm. Under erroneous positions of the satellites together with noisy TDOA measurements, the TLS algorithm provides a better solution. By running Monte-Carlo simulations, the proposed method is compared with the ordinary least squares (LS) approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.694-699
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• 2011

A closed-form technique is presented for estimating a single source location from a set of noisy time delay measurements between distributed sensors. The localization formula is derived from nonlinear least squares minimization over the unknowns of target range and bearing in polar coordinates. Computer simulation results are provided for the purpose of performance analysis. Constrained least squares minimization method with prior source location information is also discussed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.16-23
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• 2010

In this paper, we propose an efficient estimation algorithm to find unknown location of an earth station for a geostationary satellite system. A cross ambiguity function (CAF), using time difference of arrival (TDOA) and frequency difference arrival (FDOA), is usually used to estimate the unknown location of an unauthorized earth station which may invoke interference to the existing satellite systems. However, a practical estimation of the location data requires tremendous computational time of CAF, and this prohibits direct utilization of CAF. For this reason, we propose a computationally efficient algorithm which utilizes characteristics of TDOA and FDOA within CAF. The proposed algorithm greatly enhances the computational efficiency without any performance degradation. In addition, we demonstrate the simulation results on the estimation performance by the resolution of the CAF estimation. The results provided in this paper will be utilized at the real system implementation.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.1-8
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• 2013

In the next generation of ATM, ADS-B(Automatic Dependent Surveillance-Broadcast) and multilateration are the main technology recommended by ICAO(International Civil Aviation Organization). However, there are a lot of non-equipped ADS-B aircraft today. Therefore, TIS-B(Traffic Information Service-Broadcast) provides traffic information, which has obtained from radars for non-equipped ADS-B aircraft. In this paper, we presented an onboard multilateration system for non-equipped ADS-B aircraft using SSR(Secondary Surveillance Radar) signal instead of TIS-B. TIS-B has a lot of error because of using radar data, but multilateration has less error than radar because of using TDOA(Time Difference of Arrival) method. Results of performance analysis show that the position accuracy is improved by the proposed method using on-board multilateration.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.578-585
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• 2012

CNS/ATM(Communication Navigation Surveillance/Air Traffic Management) was adopted as a standard navigation system of 21st century. Therefore, ICAO(International Civil Aviation Organization) members are developing the technology and infrastructure of CNS/ATM. ADS-B(Automatic Dependent Surveillance-Broadcast) system and Multilateration system are being implemented in the surveillance field of CNS/ATM. Multilateration system is installed in order to complement radar system and to surveil blind areas. Also, Multilateration system using TDOA(Time Difference Of Arrival) is more accurate than radar. In this paper, we applied an IMM(Interacting Multiple Model) filter which is widely used in radar systems to the Multilateration data in order to improve the reliability of the Multilateration data. Comparisons with the original Multilateration data and the Multilateration data with the IMM filter show that the ADS-B data with the IMM filter provides a better performance: 38.37% near the airport, 20.86% around 10 miles of the airport.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.297-306
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• 2012

In this paper, we propose a Time Delay Traceback Scheme for the TDOA location estimation performance enhancement in NLOS environment and analyze the performance in various conditions. We place multiple readers in a square($300m{\times}300m$) searching area for reuse of received signal. Also, we use more active NLOS reader detection methode for NLOS error mitigation. when NLOS time delay 70 m, the number of the NLOS reader is 3 and the received sub-blinks number 3, proposed time delay trace-back scheme improve the RMSE about 16 m. From these results, we confirm that the proposed time delay traceback scheme is well-suited for the high precision location estimation to offer the location based service.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.7A
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• pp.1144-1151
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• 2001

본 연구에서는 AOA(Angle of Arrival)와 TOA(Time of Arrival) 그리고 TDOA(Time Difference of Arrival)의 추정값을 이용한 위치 추정 기법들이 설명되고 분석된다. 이들 기법들을 다중경로 페이딩 (mutipath fading)과 shadowing을 갖는 마이크로셀 환경에 적용한다면, 빠르고 예측할 수 없는 신호 레벨의 변화로 인하여 이동체의 위치를 정확히 추정하는 것은 어렵다. 따라서 본 연구에서는 수신 신호 세기(RSS: Received Signal Strength) 이외에 이동체와 기지국간의 거리, 이동체의 이동방향, 이동체의 이전위치와 같은 부정확한 다수의 파라미터를 동시에 고려하는 퍼지 다기준 (multi-criteria) 의사 결정 방법을 이용하여 이동체의 위치를 결정하는 방법을 제안한다. 시뮬레이션을 통하여, 이동체의 방향과 속도의 영향을 분석한다.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.415-417
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• 2003

TOA(Time of Arrival) 및 TDOA(Time Difference of Arrival)경우 무선국의 시간동기화를 위해서 고도의 기술을 요구하고 있으며, 시간동기오차에 따른 위치검지의 정밀도가 낮아지는 문제가 있어 이를 극복하기 위하여 위상차를 이용한 새로운 열차검지기법의 제안에 따른 구현을 위하여 무선장치 설계에 대하여 기술하고자 한다. 본 시스템은 전파의 전달 속도($\lambda$)를 응용하여 기준 주파수인 1.5MHz를 송신 시스템과 수신 시스템의 기준 주파수와 비교하여 그 위상의 차이를 비교하여 지연된 시간을 구한 후 이를 거리로 환산하는 시스템으로서 무선장치와 S/W로 구분하여 구현 설계하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1022-1027
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• 1999

This paper proposes method that uses Time-Difference-of-Arrival(TDOA) of Forward Pilot signals from base stations(BS) arriving at a mobile station(MS) as a position location method of CDMA MS. MS searcher does acquisition of BS Pilot signals and measurement of TDOAs. In order to do it, its processing gain is very important. Proportional relationship of the gain to the signal coherent integration interval is theoretically derived and analyzed and field test is performed to show acquisition of weak Pilot signals and stable measurements of TDOA values by increasing the gain. Also, signal strength decrease exponentially by the distance it travels. Therefore, improvement of the searcher gain makes possible to acquire Pilot signals at a location far away from BS. Variation of possible position estimation area relative to the signal strength within a cell is simulated with computer. Neglecting shadow effect it indicated necessity of detecting signals below -35dB in order to cover over 90% of cell area. Thus, efforts to maximize searcher coherent integration interval in order to acquire weak Pilot signals are required for expansion of position estimation area and measurement of stable TDOA values.

• Convergence Security Journal
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• v.22 no.2
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• pp.105-114
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• 2022

This paper is presents an intelligent control system that visualizes the direction of arrival for hearing impaired using personal mobility, and aims to recognize and prevent dangerous situations caused by sound such as alarm sounds and crack sounds on roads. The position estimation method of sound source uses a machine learning classification model characterized by generalized correlated phase transformation based on time difference of arrival. In the experimental environment reproducing the road situations, four classification models learned after extracting learning data according to wind speeds 0km/h, 5.8km/h, 14.2km/h, and 26.4km/h were compared with grid search cross validation, and the Muti-Layer Perceptron(MLP) model with the best performance was applied as the optimal algorithm. When wind occurred, the proposed algorithm showed an average performance improvement of 7.6-11.5% compared to the previous studies.