• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.3
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• pp.152-156
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• 2010

Non-line-of-sight (NLOS) propagation is one of the challenges in radio positioning. Distinguishing the transmission status of the communication as line-of-sight (LOS) or NLOS is of great importance for the wireless communication systems. This paper focuses on the identification of NLOS based on time-of-arrival (TOA) distance estimates and the received signal strength (RSS) measurements. We set a path loss threshold based on the joint TOA and RSS based NLOS detection method to determine LOS or NLOS. Simulation results show that the proposed method ensures the correct of detection for the LOS condition and can improve the NLOS identification for the weak noise and long distance.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.962-967
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• 2006

Indoor positioning is highlighted recently, and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are classified into time-based and angle-based one. This paper presents the error analysis of time-based and angle-based location methods. Because measurements of these methods are nonlinear, linearizations are needed in both cases to estimate the user position. In the linearization, Gauss-Newton method is used in both cases. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2326-2332
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• 2011

eLoran is enhanced Loran-C and eLoran is researched for as GPS backup system because this system is resistant to signal interference and has high accuracy. TOA measurements of eLoran include errors proportional to the range such as PF, SF, ASF and EF. Therefore these error factors must be compensated for improved accuracy of position. Generally, error models or GPS aided compensation methods are used, but these methods are limited by lack of infrastructure or system performance. Therefore, this paper proposes new model of error factors included in eLoran TOA measurements and navigation algorithm using this model. Error factors in this model are sum of a certain size of error and error proportional to the range. And feasibility and performance of proposed navigation algorithm are verified by using raw measurements.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.2
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• pp.108-116
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• 2011

Non-line-of-sight (NLOS) error is the most common and also a major source of errors in wireless location system. A novel weighting factor (NWF) method is presented in this paper, based on the RSS(Received Signal Strength) measurements, path loss model and Circular Disk of Scatterers Model (CDSM). The proposed positioning method effectively weighted the TOA distance measurements for each Base Station (BS). Simulation results show that the proposed method efficiently weighted the distance measurements and achieve higher localization accuracy than that of Linear Line of Position (LLOP) and Believable Factor Algorithm (BFA).

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.437-443
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• 2019

In this paper, a new algorithm for the calculation of the range between an LTE base station (BS) and a user equipment (UE) using time-of-arrival (TOA) measurements of LTE signals is proposed. First, the cell identity (cell ID) of the received signal is acquired using the primary synchronization signal (PSS) and secondary synchronization signal (SSS) to identify the BS transmitted the signal. The proposed algorithm exploits the cell-specific reference signal (CRS), the reference sequence inserted in commercial LTE signals, to estimate the time delay using 2D cross-correlation. The obtained TOA estimations can be used to calculate the range employed from the known BS location. The performance of the proposed algorithm is evaluated with the experiment performed using real LTE signals transmitted from the commercial BS.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.535-549
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• 2008

Vicarious calibration for the satellite sensor relies on simulated TOA (Top-of-Atmosphere) radiances over various targets. In this study, TOA visible radiance was calculated over ocean targets which are located in five different regions over the Indian and Pacific ocean, and its possible use for the satellite sensor calibration was examined. TOA radiances are simulated with the 6S radiative transfer model for the comparison with MODIS/Terra and SeaWiFS measurements. Geometric angles and sensor characteristics of the reference satellites were taken into account for the simulation. AOT (Aerosol Optical Thickness) from MODIS/Terra, pigment concentrations from Sea WiFS, and ozone amount from OMI measurements were used as inputs to the model. Other atmospheric input parameters such as surface wind and total column water vapor were taken from NCEP/NCAR reanalysis data. The 5-day averaged radiances over all targets show that the percent differences between simulated and observed radiances are within about ${\pm}5%$ in year 2005, indicating that the calculated radiances are in good agreement with satellite measurements. It has also been shown that the algorithm can produce the SeaWiFS radiances within about ${\pm}5%$ uncertainty range. It has been suggested that the algorithm can be used as a tool for calibrating the VIS bands within about 5% uncertainty range.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.996-1003
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• 2016

Trilateration technique using time of arrival(TOA) is generally used for single target position estimation in radar system. However, trilateration technique has limitation in case of multiple targets, since it is difficult to distinguish the measurements corresponding to the respective targets. In this study, to eliminate ambiguity of relation between measurements and targets, micromotion of each target is measured by micro Doppler which is actively studied in radar industry nowadays and these information are used to distinguish measurements used at trilateration technique. Resultingly, the trilateration technique is applied successfully for each target. The targets are considered as multiple submissiles separated from the missile. Simulation results shows the performance of the proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1241-1249
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• 2011

There are TOA, TDOA and AOA method to estimate the position of the electromagnetic wave transmitter by using the multiple receivers at the fixed position. Among these methods, AOA method is suitable for the jammer localization system. Because TOA method can be adopted for the clocks of the transmitter and the receiver are synchronized each other, and TDOA method can be only adopted for a broad-band jamming signal. This paper, therefore, analyzes the characteristics of the AOA measurements and the sensitivity of the positioning performance according to the system design parameters. Based on the analyzed results, the jammer localization system to meet the desired performance is designed, and it has been checked that the positioning error for the jammer located at a distance of 10km is lower than 38m through the simulation results.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.15-18
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• 2014

This paper presents a sensor location decision making method respect to Container-Grown Seedlings in view of precision agriculture (PA) when sensors involved in tree container measure received signal strength (RSS) or time-of-arrival (TOA) between themselves and neighboring sensors. A small fraction of sensors in the container-grown seedlings system have a known location, whereas the remaining locations must be estimated. We derive Rao-Cramer bounds and maximum-likelihood estimators under Gaussian and log-normal models for the TOA and RSS measurements, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2132-2143
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• 2015

This paper presents two distance geometry-based algorithms for wireless location in cellular network systems-distance geometry filtering (DGF) and distance geometry constraint (DGC). With time-of-arrival range measurements, the DGF algorithm estimates the mobile station position by selecting a set of measurements with relatively small NLOS (non-line-of-sight) errors, and the DGC algorithm optimizes the measurements first and then estimates the position using those optimized measurements. Simulation results show that the proposed algorithms can mitigate the impact of NLOS errors and effectively improve the accuracy of wireless location.