• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.103-118
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• 1999

This paper analyzes the performance of symbol timing recovery and equalizer in 8VSB digital terrestrial TV receiver under various multipath signals and proposes equalization techniques which improve indoor reception performance. Data segment sync is used for symbol timing recovery and timing offset is measured for echoes of various delays and amplitudes by using symbol timing detection filter whose pattern is +1. +1. -1. and -1. Measured timing offsets were below 10% for long echoes with more than 5 symbol delay and above 30% for short echoes with around 1 symbol delay. Indoor reception is always more challenging than outdoor reception due to lower signal strength. large and short multipaths. and moving interfering objects. So it is considered to use FSE (Fractionally Spaced Equalizer) which is very robust to timing offset and blind equalizer which can update equalizer tap coefficients even by information data. We compare the performance of conventional DFE (Decision Feedback Equalizer) and FSE-DFE using LMS algorithm and Stop and Go algorithm for the indoor reception. Experiments reveals FSE has excellent performance for large timing offset and Stop and Go algorithm shows good performance for Doppler shift. so we propose to use FSE-DFE structure with Stop and Go algorithm for the reliable indoor reception.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.263-273
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• 2008

The precision of sensors' position is particularly important in the application of road extraction or digital map generation. In general, the various ranging solution systems such as GPS, Total Station, and Laser Ranger have been employed for the position of the sensor. Basically, the ranging solution system has problems that the signal may be blocked or degraded by various environmental circumstances and has low temporal resolution. To overcome those limitations a IMU/range integrated system could be introduced. In this paper, after pointing out the limitation of extended Kalman filter which has been used for workhorse in navigation and geodetic community, the two sampling based nonlinear filters which are sigma point Kalman filter using nonlinear transformation and carefully chosen sigma points and particle filter using the non-gaussian assumption are implemented and compared with extended Kalman filter in a simulation test. For the ranging solution system, the GPS and Total station was selected and the three levels of IMUs(IMU400C, HG1700, LN100) are chosen for the simulation. For all ranging solution system and IMUs the sampling based nonlinear filter yield improved position result and it is more noticeable that the superiority of nonlinear filter in low temporal resolution such as 5 sec. Therefore, it is recommended to apply non-linear filter to determine the sensor's position with low degree position sensors.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.4 s.95
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• pp.389-396
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• 2005

In this paper, we propose a pre-distortion method using the NLMS(Normalized Least Mean Square) algorithm to cope with hish PAPR(Peak to Average Power Ratio) problem in OFDM communication system. This proposed scheme estimates the distortion characteristics of HPA, and changes the characteristic against the distortion. Therefore, it can be shown that the adaptive characteristic of the NLMS pre-distorter is good to track the various nonlinear characteristic of HPA, even though HPA characteristic is changed by temperature variation or aging. From the performance analysis, SNR efficiency of NLMS pre-distorter is about $0.5\;\cal{dB}$ less than that of common numerical non-adaptive pre-distorter, when IBO(Input Back Off) is $0\;\cal{dB}$. However, the NLMS pre-distorter is better than the common numerical pre-distorter, because these two pre-distorters have similar performance in higher than $3\;\cal{dB}$ IBO, and the NLMS pre-distorter maintains the constant performance even though characteristic of HPA is changed.