• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.590-593
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• 2004

Extraction of ocean surface current velocity offers important physical oceanographic parameters especially on understanding ocean environment. Although Remote Sensing techniques were highly developed, the investigation of ocean surface current using Synthetic Aperture Radar (SAR) is not an easy task. This paper presents the results of ocean surface current observation using Doppler Centroid of ERS-1 SAR data obtained off the coast of Korea peninsula. We employed the concept, in which Doppler frequency shift and the ocean surface current are closely related, to evaluate ocean surface current. Moving targets cause Doppler frequency shift of the back scattered radar waves of SAR, thus the line-of-sight velocity component of the scatters can be evaluated. The Doppler frequency shift can be measured by estimating the difference between Doppler Centroid of raw SAR data and reference Doppler Centroid. Theoretically, the Doppler Centroid is zero; however, squinted antenna which is affected by several physical factors causes Doppler Centroid to be nonzero. The reference Doppler Centroid can be obtained from measurements of sensor trajectory, attitude and Earth model. The estimated Doppler Centroid was compensated by considering the accurate attitude estimation of ERS-1 SAR. We could verify the correspondence between the estimated ocean surface current and observed in-situ data in the error bound.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.11-20
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• 2013

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.421-430
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• 2007

This paper presents the results of the ocean surface current velocity estimation using 6 Radarsat-1 SAR images acquired in west coastal area near Incheon. We extracted the surface velocity from SAR images based on the Doppler shift approach in which the azimuth frequency shift is related to the motion of surface target in the radar direction. The Doppler shift was measured by the difference between the Doppler centroid estimated in the range-compressed, azimuth-frequency domain and the nominal Doppler centroid used during the SAR focusing process. The extracted SAR current velocities were statistically compared with the current velocities from the high frequency(HF) radar in terms of averages, standard deviations, and root mean square errors. The problem of the unreliable nominal Doppler centroid for the estimation of the SAR current velocity was corrected by subtracting the difference of averages between SAR and HF-radar current velocities from the SAR current velocity. The corrected SAR current velocity inherits the average of HF-radar data while maintaining high-resolution nature of the original SAR data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.629-632
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• 2007

While conventional interferometric SAR (InSAR) technique is an excellent tool for displacement observation, it is only sensitive to one-dimensional deformation along the satellite's line-of-sight (LOS). Recently, a multiple aperture interferogram (MAI) technique has been developed to overcome this drawback. This method successfully extracted along-track displacements from InSAR data, based on split-beam InSAR processing, to create forward- and backward- looking interferograms, and was superior to along-track displacements derived by pixel-offset algorithm. This method is useful to measure along-track displacements. However, it does not only decrease the coherence of MAI because three co-registration and resampling procedures are required for producing MAI, but also is confined to a suitable interferometric pair of SAR images having zero Doppler centroid. In this paper, we propose an efficient and robust method to generate MAI from interferometric pair having non-zero Doppler centroid. The proposed method efficiently improves the coherence of MAI, because the co-registration of forward- and backward- single look complex (SLC) images is carried out by time shift property of Fourier transform without resampling procedure. It also successfully removes azimuth flat earth and topographic phases caused by the effect of non-zero Doppler centroid. We tested the proposed method using ERS images of the Mw 7.1 1999 California, Hector Mine Earthquake. The result shows that the proposed method improved the coherence of MAI and generalized MAI processing algorithm.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.421-430
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• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• Current Optics and Photonics
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• v.3 no.5
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• pp.466-472
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• 2019

A system for continuous-wave coherent Doppler lidar (CW lidar), made up of all-fiber structures and a coaxial transmission telescope, was set up for wind measurement in Hefei (31.84 N, 117.27 E), Anhui province of China. The lidar uses a fiber laser as a light source at a wavelength of $1.55{\mu}m$, and focuses the laser beam on a location 80 m away from the telescope. Using the CW lidar, radial wind measurement was carried out. Subsequently, the spectra of the atmospheric backscattered signal were analyzed. We tested the noise and obtained the lower limit of wind velocity as 0.721 m/s, through the Rayleigh criterion. According to the number of Doppler peaks in the radial wind spectrum, a classification retrieval algorithm (CRA) combining a Gaussian fitting algorithm and a spectral centroid algorithm is designed to estimate wind velocity. Compared to calibrated pulsed coherent wind lidar, the correlation coefficient for the wind velocity is 0.979, with a standard deviation of 0.103 m/s. The results show that CW lidar offers satisfactory performance and the potential for application in wind measurement.

• Korean Journal of Remote Sensing
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• v.18 no.5
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• pp.273-280
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• 2002

This paper describes a mathematical model and its utilization algorithm for calculating the accurate target position on the ellipsoidal earth surface which corresponds to a range-azimuth coordinates of unprocessed synthetic aperture radar (SAR) images. A geometrical model which is a set of coordinate transformations is described. The side-looking directional angle (off-nadir angle) is determined in an iterative fashion by using the model and the accurate slant range which is calculated from the range sampling timing of the instrument. The algorithm can be applied not only for the geolocation of SAR images but also for the high quality SAR image generation by calculating accurate Doppler parameters.

• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.183-196
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• 1998

The Synthetic Aperture Radar(SAR) image and the Digital Elevation Model(DEM) of an target area are put into use to generate three dimensional image map. An method of image map generation is explained. The orbit and attitude determination of satellite makes it possible to model signal acquisition configuration precisely, which is a key to mapping image coordinates to geographic coordinates of concerned area. An application is made to RADARSAT in the purpose of testing its validity. To determine the orbit, zero Doppler range is used. And to determine the attitude, Doppler centroid frequency, which is the frequency observed when target is put in the center of antenna's view, is used. Conventional geocoding has been performed on the basis of direct method(mapping image coordinates to geographic coordinates), but in this reserch the inverse method(mapping from geographic coordinates to image coordinates) is taken. This paper shows that precise signal acquisition modeling based on the orbit and attitude determination of satellite as a platform leads to a satellite-centered accurate geocoding process. It also shows how to model relative motion between space-borne radar and target. And the relative motion is described in ECIC(earth-centered-initial coordinates) using Doppler equation and signal acquisition geometry.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.163-171
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• 2005

I have developed a processor for synthetic aperture radar (SAR) raw data compression using range-doppler algorithm for educational purpose. The program realized a generic SAR focusing algorithm so that it can deal with any SAR system if the specification is known. It can run efficiently on a low-cost computer by selecting minimum size out of a whole dataset, and can produce intermediate images during the process. Especially, the program is designed for educational purpose in such a way that Doppler centroid and azimuth ambiguity can be determined graphically by the user. By distributing the source code and the algorithm to public, I intend to maximize the educational effect on understanding and utilizing SAR data. This paper introduces the principle of SAR focusing algorithm embedded on the eSAR processor and shows an example of data processing using ERS-1 raw data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1166-1179
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• 2013

In wireless sensor network (WSN) environments, environmental noises are generated by, for example, small passing animals, crickets chirping or foliage blowing and will interfere target detection if the noises are higher than the sensor threshold value. For accurate tracking by acoustic WSNs, these environmental noises should be filtered out before initiating track. This paper presents the effect of environmental noises on target tracking and proposes a new algorithm for the noise mitigation in acoustic WSNs. We find that our noise mitigation algorithm works well even for targets with sensing range shorter than the sensor separation as well as with longer sensing ranges. It is also found that noise duration at each sensor affects the performance of the algorithm. A detection algorithm is also presented to account for the Doppler effect which is an important consideration for tracking higher-speed ground targets. For tracking, we use the weighted sensor position centroid to represent the target position measurement and use the Kalman filter (KF) for tracking.