• 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.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.146-150
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• 2015

The COSPAS-SARSAT committee decides MEOSAR (Medium-Earth Orbit for search and rescue) service development for installing 406MHz SAR instruments on their respective MEO navigation satellite system of the United States, EU, and Russia, since 2000. The transmitted beacon signal is separately arrived by satellites with different FOA (Frequency of Arrival) and TOA (Time of Arrival). It is directly transferred to MEOLUT. In MEOLUT, a LUT track at least 3 or 4 satellites simultaneously and estimate location of beacon using time difference of arrival (TDOA) and frequency difference arrival (FDOA). But the transmitted distress signals may be overlapped each other because the distress beacons transmit signal on mean interval of 50 seconds in arbitrary time. It's difficult that simultaneously estimate location of beacon by current scheme for several overlapped distress signal. So we use cross ambiguity function (CAF) Map algorithm and present Multi-CAF MAP scheme in order to satisfy performance requirement of system. The performance is analyzed for COSAPS-SARSAT MEOSAR.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.15-21
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• 2020

This paper presents the outlier detection algorithm in the estimation method of a source location and velocity based on two-step weighted least-squares method using time difference of arrival(TDOA) and frequency difference of arrival(FDOA) data. Since the accuracy of the estimated location and velocity of a moving source can be reduced by the outliers of TDOA and FDOA data, it is important to detect and remove the outliers. In this paper, the method to find the minimum inlier data and the method to determine whether TDOA and FDOA data are included in inliers or outliers are presented. The results of numerical simulations show that the accuracy of the estimated location and velocity is improved by removing the outliers of TDOA and FDOA data.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.154-159
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• 2019

When measuring the radiating noise of an underwater moving source, the range information between the acoustic source and the receiver is an important evaluation factor, and the measurement standards such as a receiver position, a moving source depth and a speed are set. Although there is a method of using the cross correlation as a method of finding the range of the underwater moving source, this method requires a time synchronization process. In this paper, we proposed the method to estimate the range by comparing the Doppler frequency difference of the theoretically calculated multipath signal with the Doppler frequency difference of the multipath signal estimated from the received signal. The proposed method does not require a separate time synchronization process. Simulations were performed to verify the performance, and the ranging error of the proposed method reduced by about 95 % than that of the conventional method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.10
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• pp.907-911
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• 2007

This paper dealt with the frequency spectrum analysis of acoustic signal produced by partial discharge (PD) in insulation oil and the positioning of PD occurrence to apply in diagnosis of oil insulated transformers. Three types of electrode system ; the needle-plane, the plane-plane, and the wire-wire structure were assembled to simulate partial discharges in oil insulated transformers. A low-noise amplifier and a decoupling circuit were designed to detect acoustic signal with high sensitivity The frequency spectrum of the acoustic signal were 50 kHz ${\sim}$ 260 kHz in the needle-plane, 50 kHz ${\sim}$ 250 kHz in the plane-plane, and 45 kHz${\sim}$195 kHz in the wire-wire electrode system. Their peak frequencies were 145 kHz, 130 kHz and 114 kHz, respectively The position of PD occurrence was calculated by the time difference of arrival (TOA) using three acoustic emission (AE) sensors, and we could find the position within the error of 1 % in the experimental apparatus.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4A
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• pp.291-301
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• 2009

In this paper, the effect of ISI(Inter-Symbol Interference) and ICI(Inter-Carrier Interference) due to time difference of arrival on OFDMA-based mobile multi-hop relay (MMR) systems is analyzed. Analyses are performed for the ISI caused by the previous OFDMA symbol transmitted from neighboring macro or relay cell as well as the ISI caused by the next OFDMA symbol transmitted from neighboring macro or relay cell. Then, an effective SINR(Signal to Interference plus Noise Ratio) estimation method and a path selection method considering time difference of arrival are proposed to minimize the effect of ISI and ICI. It is shown by simulation that the performance degradation caused by time difference of arrival can be significantly mitigated when the proposed path selection method is applied to the uplink of OFDMA-based MMR systems.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1861-1867
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• 2010

This paper described the positioning algorithm of partial discharge in insulation oil by acoustic method for the application of an on-line diagnosis in oil-immersed transformers. In the experiment, five AE sensors having the resonant frequency of 150 kHz were used, and a signal conditioner was fabricated. A needle-plane electrode system which is composed of a needle with a curvature radius of $10{\mu}m$ and a plane electrode with a diameter of 60 mm was installed to simulate partial discharges in insulation oil. From the time difference of arrival (TOA) of acoustic signal, we calculated the location of partial discharge in insulation oil. In the experiment, an algorithm of positioning of PD occurrence by the time difference of arrival was proposed. From the experimental results, the positioning error of PD calculated by three AE sensors was within 4%.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.589-594
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• 2015

In this paper, we described the Cramer-Rao Lower Bound (CLRB) performances of Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) methods when there are multiple emitters. The TDOA and FDOA values between two receivers can be simultaneously estimated by using the so-called Complex Ambiguity Function (CAF). In the case of multiple emitters, there exist Inter Symbol Interferences (ISIs) in the measurement data. Therefore, it is required to reduce the effect of ISI and provide a performance evaluation method of TDOA and FDOA estimations. In order to eliminate the ISIs, using of a filter bank before calculating CAF is proposed when the carrier frequencies of the emitters are different to one another. Angle of Arrival (AOA) or Received Signal Strength (RSS) methods before calculating CAF were proposed to reduce the ISIs when the carrier frequencies are the same. In order to evaluate the CRLB of TDOA and FDOA estimations, we employed the conditional probability distribution method and described the numerical comparison results.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.