• Proceedings of the KSRS Conference
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• v.1
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• pp.17-20
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• 2006

Three HF ocean radar stations were installed at the Soya/La Perouse Strait in the Sea of Okhotsk in order to monitor the Soya Warm Current. The frequency of the HF radar is 13.9 MHz, and the range and azimuth resolutions are 3 km and $5^{\circ}$, respectively. The radar covers a range of approximately 70 km from the coast. It is shown that the HF radars clearly capture seasonal and short-term variations of the Soya Warm Current. The velocity of the Soya Warm Current reaches its maximum, approximately 1 m $s^{-1}$, in summer, and weakens in winter. The velocity core is located 20 to 30 km from the coast, and its width is approximately 50 km. The surface transport by the Soya Warm Current shows a significant correlation with the sea level difference along the strait, as derived from coastal tide gauge records. The cross-current sea level difference, which is estimated from the sea level anomalies observed by the Jason-1 altimeter and a coastal tide gauge, also exhibits variation in concert with the surface transport and along-current sea level difference.

• Proceedings of the KSRS Conference
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• v.2
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• pp.672-675
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• 2006

The geostrophic current component is estimated from the sea surface velocity observed by the long-range High-Frequency Ocean Radar (HF radar) system in the upstream of the Kuroshio, by comparing with geostrophic velocity determined from along-track T/P and Jason-1 altimetry data. However, the sea surface velocity of the HF radar (HF velocity) contains not only the geostrophic current but also the ageostrophic current such as tidal current and wind-driven Ekman current. Tidal current component is first extracted by the harmonic analysis of the time series of the HF velocity. Then, the Ekman current is further estimated from daily wind data of IFREMER by applying the least-square method to the residual difference between the HF velocity and the altimetry geostrophic velocity. As a result, the Ekman current in the HF velocity is estimated as 1.32 % of the wind speed and as rotated 45$^{\circ}$ clockwise to the wind direction. These parameters are found almost common in the Kuroshio area and in the Open Ocean. After these corrections, the geostrophic velocity component in the HF velocity agrees well with the altimetry geostrophic velocity.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.108-117
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• 2003

In this paper, two types of radar vehicle detectors compatible with currently being used ILD(Inductive Loop Detector) without any modification has been developed. With these vehicle detectors based on FMCW altimeter and Doppler speedometer techniques at 24 GHz, the length and speed of a vehicle can be detected. For signal processing part, we have used DAQ board and programmed with LabView. For compatibility with traffic information network connected with existing ILD's, traffic information has been sent to VDS by using RS-232C standard interface. This development has improved approximately 10% in accuracy in terms of the speed and length information compared with that of the installed ILD in the test field.

• Proceedings of the KSEEG Conference
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• 2000.04b
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• pp.140-142
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• 2000

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.297-305
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• 2001

Ocean satellite altimetry-implied free-air gravity anomalies have had the shortest wavelengths removed during the processing to generate the optimal solution between multiple radar altimeter missions. ERS-1 168day mission altimetry was residualized to a reference geoid surface generated by integrating Anderson & Knudsen’s free-air gravity anomalies for the Barents Sea. The altimetry tracks were reduced and filtered to extract the shortest wavelengths (between 4 and 111 km) from both ascending and descending tracks, respectively. These data were recombined using existing quadrant-swapping techniques in the wavenumber domain to generate a correlated, high frequency gravity field related to the local geologic sources. This added-value surface adjusted the reference free-air gravity anomalies to better reflect features in the gravity field at a wavelength related to the distance between altimetry ground tracks.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.406-414
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• 2014

In this paper, it is introduced characteristics of FMCW-type Radar Altimeter for KUH, and its defects occurred during ground/flight test in initial product phase. In addition, it is also described 'data/control flow model' based fault analysis results of S/W and processes of verifying improvement design through flight test as well as aircraft system integration test called MEP SIL. As a result of design improvement and verification, it is validated that settling the defects and improving not only safety but also capability of the KUH.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.171-179
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• 2002

Sampling rates become inconsistent when spatial data in the spherical coordinate are resampled with respect to latitudinal or longitudinal degree for mathematical processes such as Fourier Transform, and this results in distortions of the processed data in the wavenumber domain. These distortions are more evident in the polar regions. An example is presented to show such distortions during the recovery process of free-air gravity anomalies from ERS-1 satellite radar altimeter data from the Barents Sea in the Russian Arctic, and a method is presented to minimize the distortion using the Lambert Conformal Conic map projection. This approach was found to enhance the free-air gravity anomalies in both data and wavenumber domains.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.448-453
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• 2002

Remote sensing technology is one of the most powerful tools for human to know the nature and their living environment. However, before microwave remote sensing was developed and applied, remote sensing application was limited strongly by weather and time. Microwave remote sensing technology solves the problem. It makes us to have the capability to acquire information at all time of the day and under all weather condition, and make remote sensing technology be used in more wider area. Microwave remote sensing system include mainly Synthetic Aperture Radar (SAR), Microwave Radiometer, Microwave Scatterometer, and Altimeter (ALT). As SAR can acquire image whose spatial resolution is similar with visible and infrared image, it is paying much attention to and playing a more and more important role in earth observation. In recent year, the development of new SAR technology (multi-band and multi-polarization technology, InSAR technology, D-InSAR technology, and so on) makes SAR remote sensing go to an new stage, and its application area become more and more widely. The first Synthetic Aperture Radar (SAR) in the world appeared in 1960. After that, SAR and its application all developed very fast. Some radar satellites launched and run (include Seasat-A in 1978, ERS-1 in 1991, JERS-1 in 1992, Radarsat in 1995, and so on) promote SAR research and application in world greatly. China began to develop its SAR sensor and research SAR application in 1970s. After more than 30 years' research, it get some important development in sensor development data processing method, and application. Some operational systems have been used and play an important role. This paper will introduce the development of SAR technology and its application in China.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.375-383
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• 2001

We extracted sea surface heights(SSH) from the TopexJPoseidon(T/P) radar altimeter data to compare with fhe SSH estimated from in-situ lide gauges(T/G) at Ulleungdo, Pohang, and SockcholMucko sites. Selection criteria such as wet/dry troposphere, ionosphere, and ocean tide were used to estimate accurate SSH. For time series analysis, the one-hour interval tide gauge SSHs were resampled al lO-day interval of the satellite SSHs. The ocean tide model applied in the altimeter data processing showed periodic aliasings of 175.5 day, 87.8 day, 62J day, 58.5 day, 49.5 day and 46.0 day, and, hence, the ZOO-day filtering was applied to reduce these spectral noises. Wavenumber correlation analysis was also applied to extract common components between the two SSHs, resulting in enhancing the correlation coefficient(CC) dramatically. The original CCs between the satenite and tide gauge SSHs are 0.46. 0.26, and 0.]5, respectively. Ulleungdo shows the largest cc bec;luase the site is far from the coast resulting in the minimun error in the satellite observations. The CCs were then increased to 0.59, 030, and 0.30, respectively, after 200.day filtering, and to 0.69, 0.63. and 0.59 after removing inversely correlative components using wavenumber correlation analysis. The CCs were greatly increased by 87, 227, and 460% when the wavenumber correlation analysis was followed by 2oo-day filtering, resulting in the final CCs of 0.86, 0.85, 0.84, respectively. It was found that the best SSHs were estimated when the two methods were applied to the original data. The low-pass filtered TIP SSHs were found to be well correlated with the TIG SSHs from tide gauges, and the best correlation results were found when we applied both low-pass filtering and spectral correlation analysis to the original SSHs.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.32-40
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• 2015

In this paper, the optimum antenna placement is analyzed by considering the interference between airborne antennas mounted on the unmanned aerial vehicle(UAV). The analysis is implemented by selecting the antennas that the distance and operational frequency band between airborne antennas is close to each other among the omni-directional antennas. The analyzed antennas are the control datalink, TCAS(Traffic Collision & Avoidance System), IFF(Identification Friend or Foe), GPS(Global Positioning System), and RALT(Radar ALTimeter) antennas. There are three steps for the optimum antenna placement analysis. The first step is selecting the antenna position having the optimum properties by monitoring the variation of radiation pattern and return loss by the fuselage of UAV after selecting the initial antenna position considering the antenna use, type, and radiation pattern. The second one is analyzing the interference strength between airborne antennas considering the coupling between airborne antennas, spurious of transmitting antenna, and minimum receiving level of receiving antenna. In case of generating the interference, the antenna position without interference is selected by analyzing the minimum separation distance without interference. The last one is confirming the measure to reject the frequency interference by the frequency separation analysis between airborne antennas in case that the intereference is not rejected by the additional distance separation between airborne antennas. This analysis procedure can be efficiently used to select the optimum antenna placement without interference by predicting the interference between airborne antennas in the development stage.