• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.287-293
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• 2018

This paper presents a satellite relative navigation strategy for formation flying, which chooses an appropriate navigation algorithm according to the operating environment. Not only global positioning system (GPS) measurements, but laser measurements can also be utilized to determine the relative positions of satellites. Laser data is used solely or together with GPS measurements. Numerical simulations were conducted to compare the relative navigation algorithm using only laser data and laser data combined with GPS data. If an accurate direction of laser pointing is estimated, the relative position of satellites can be determined using only laser measurements. If not, the combined algorithm has better performance, and is irrelevant to the precision of the relative angle data between two satellites in spherical coordinates. Within 10 km relative distance between satellites, relative navigation using double difference GPS data makes more precise relative position estimation results. If the simulation results are applied to the relative navigation strategy, the proper algorithm can be chosen, and the relative position of satellites can be estimated precisely in changing mission environments.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.677-692
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• 2011

Suspended sediment is an important oceanic variable for monitoring changes in coastal environment related to physical and biogeochemical processes. In order to estimate suspended sediment concentration (SSC) from satellite data, we derived SSC coefficients by fitting satellite remote sensing reflectances to in-situ suspended sediment measurements. To collect in-situ suspended sediment, we conducted ship cruises at 16 different locations three times for the periods of Sep.-November 2009 and Jul. 2010 at the passing time of Landsat $ETM_+$. Satellite data and in-situ data measured by spectroradiometers were converted to remote sensing reflectances ($R_{rs}$). Statistical approaches proved that the exponential formula using a single band of $R_{rs}$(565) was the most appropriate equation for the estimation of SSC in this study. Satellite suspended sediment using the newly-derived coefficients showed a good agreement with insitu suspended sediment with an Root Mean Square (RMS) error of 1-3 g/$m^3$. Satellite-observed SSCs tended to be overestimated at shallow depths due to bottom reflection presumably. This implies that the satellite-based SSCs should be carefully understood at the shallow coastal regions. Nevertheless, the satellite-derived SSCs based on the derived SSC coefficients, for the most cases, reasonably coincided with the pattern of in-situ suspended sediment measurements in the study region.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.280-289
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• 2008

An extensive set of both in-situ and satellite data regarding oceanic sea surface temperatures in Northeast Asian seas, collected over a 10-year period, was collocated and surveyed to assess the accuracy of satellite-observed sea surface temperatures (SST) and investigate the characteristics of satellite measured SST errors. This was done by subtracting insitu SST measurements from multi-channel SST (MCSST) measurements. 845 pieces of collocated data revealed that MCSST measurements had a root-mean-square error of about 0.89$^{\circ}C$ and a bias error of about 0.18$^{\circ}C$. The SST errors revealed a large latitudinal dependency with a range of $\pm3^{\circ}C$ around 40$^{\circ}N$, which was related to high spatial and temporal variability from smaller eddies, oceanic currents, and thermal fronts at higher latitudes. The MCSST measurements tended to be underestimated in winter and overestimated in summer when compared to in-situ measurements. This seasonal dependency was discovered from shipboard and moored buoy measurements, not satellite-tracked surface drifters, and revealed the existence of a strong vertical temperature gradient within a few meters of the upper ocean. This study emphasizes the need for an effort to consider and correct the significant skin-bulk SST difference which arises when calculating SST from satellite data.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.98-98
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• 2004

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.616-624
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• 2013

When jamming signal is received, there would be malfunctions in GPS-based precise location systems. Especially, in aviation fields, these malfunctions may lead to more serious damages. Naturally, there are some research results about the prevention or location method for one jammer, but it is hard to identify and obtain measurements when multiple and various type signals are received. Therefore, we propose a method of identification and measurements acquisition algorithm in order to localize the multiple jammers which transmit CW, DSSS and SCW type signals. Also, a computer simulation is carried out so as to validate the feasibility of the proposed method by using MATLAB. From the simulation results, it is confirmed that the proposed method successfully identified the signal type and acquired the measurements of CW, DSSS and SCW type signals.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.7-14
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• 2012

Due to inaccurate safe navigation estimates, maritime accidents have been occurring consistently. In order to solve this, the precise positioning technology using carrier phase information is used, but due to high buildings near inland waterways or inclination, satellite signals might become weak or blocked for some time. Under this weak signal environment for some time, the GPS raw measurements become less accurate so that it is difficult to search and maintain the integer ambiguity of carrier phase. In this paper, a method to generate code and carrier phase measurements under this environment and maintain resilient navigation is proposed. In the weak signal environment, the position of the receiver is estimated using an inertial sensor, and with this information, the distance between the satellite and the receiver is calculated to generate code measurements using IGS product and model. And, the carrier phase measurements are generated based on the statistics for generating fractional phase. In order to verify the performance of the proposed method, the proposed method was compared for a fixed blocked time. It was confirmed that in case of a weak or blocked satellite signals for 1 to 5 minutes, the proposed method showed more improved results than the inertial navigation only, maintaining stable positioning accuracy within 1 m.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.461-474
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• 2020

Korea launched Geostationary Environmental Monitoring Satellite (GEMS), a UV/visible spectrometer that measure pollution gases on 18 February 2020. Because satellite retrieval is an ill-posed inverse solving process, the validation with ground-based measurements or other satellite measurements is essential to obtain reliable products. For this purpose, satellite-based OMI and OMPS total column ozone (TCO), and ground-based Pandora TCO in Busan and Seoul were selected for future GEMS validation. First of all, the goal of this study is to validate the ground ozone data using characteristics that satellite data provide coherent ozone measurements on a global basis, although satellite data have a larger error than the ground-based measurements. In the cross validation between Pandora and OMI TCO, we have found abnormal deviation in ozone time series from Pandora #29 observed in Seoul. This shows that it is possible to perform inverse validation of ground data using satellite data. Then OMPS TCO was compared with verified Pandora TCO. Both data shows a correlation coefficient of 0.97, an RMSE of less than 2 DU and the OMPS-Pandora relative mean difference of >4%. The result also shows the OMPS-Pandora relative mean difference with SZA, TCO, cross-track position and season have insignificant dependence on those variables.In addition, we showed that appropriate thresholds depending on the spatial resolution of each satellite sensor are required to eliminate the impact of the cloud on Pandora TCO.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.1-15
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• 2018

Passive microwave sea surface temperatures (SST) were validated in the Northwest Pacific using a total of 102,294 collocated matchup data between Global Precipitation Measurement (GPM) / GPM Microwave Sensor(GMI) data and oceanic in-situ temperature measurements from March 2014 to December 2016. A root-mean-square (RMS) error and a bias error of the GMI SST measurements were evaluated to $0.93^{\circ}C$ and $0.05^{\circ}C$, respectively. The SST differences between GMI and in-situ measurements were caused by various factors such as wind speed, columnar atmospheric water vapor, land contamination near coastline or islands. The GMI SSTs were found to be higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. As the wind speed increased at night, SST errors showed positive bias. In addition, other factors, coming from atmospheric water vapor, sensitivity degradation at a low temperature range, and land contamination, also contributed to the errors. One of remarkable characteristics of the errors was their latitudinal dependence with large errors at high latitudes above $30^{\circ}N$. Seasonal characteristics revealed that the errors were most frequently observed in winter with a significant positive deviation. This implies that SST errors tend to be large under conditions of high wind speeds and low SSTs. Understanding of microwave SST errors in this study is anticipated to compensate less temporal capability of Infrared SSTs and to contribute to increase a satellite observation rate with time, especially in SST composite process.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.113-120
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• 2005

Oceanographic measurements from Ieodo Ocean Research Station and its vicinity were compared for assessment and mutually adjusted with satellite data. From the Topex/Poseidon and ERS-1/2 radar altimeter and scatterometer data, sea surface height, wind speed and direction were extracted and analyzed. Shipborne wind direction data acquired in June 1995 show good coherence with the satellite data, while sea surface height and wind speed show differences, possibly resulting from the distance between the measurement points. This can be improved by analyzing more satellite data or using other available shipborne data. The recent 3 months of Ieodo Station data between December 2004 and February 2005 were also analyzed and compared with the satellite data. The Ieodo Station data were found to have considerable gaps during the period as well as seriously biased particular when the data were averaged with some abnormal data. The Ieodo Station and satellite data were then mutually adjusted on the basis of their statistics. Ieodo Station oceanographic measurements are very efficient for ground-frothing of satellite data because they are stationary and the station is located far from the coast. On the other hand, the satellite measurements are the only data to fill up gaps and adjust biases of the Ieodo Station data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.374-377
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• 2005

The distribution and changes of tropospheric nitrogen dioxide ($NO_2$) are analyzed using the satellite measurements data from GOME (Global Ozone Monitoring Experiment) and SCIMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY). We produced global maps of tropospheric $NO_2$ for 4 seasons using GOME measurements from January 1997 to June 2003. The global distribution shows high values in regions with dense population and high industrialization. Tropospheric $NO_2$ shows obvious seasonal changes depending on its emission and lifetime. Based on the good agreement between two instruments in the time period of overlapping measurements (January 2003-June2003), we linked SClAMACHY data to the GOME time series. The combined time series over the past decade indicate that $NO_2$ 1evels over China are rapidly increasing while those over Europe are decreasing. We also discussed potential application of spaceborne instruments in detecting and characterizing long-distance transport of $NO_2$.