• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.100-107
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• 2009

Velocity estimation is one of important issues for efficient system management in mobile cellular systems. In this paper, a modified velocity estimation scheme which works in Adaptive Antenna System (AAS) is proposed. The proposed scheme estimates user velocity based on moving distance information and sojourn time information. From numerical results, it is shown that the proposed scheme can estimate user velocity accurately with low cost.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.59-61
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• 2004

For automatic landing of small VTOL UAV, it is necessary to calculate the distance from the UAV and the ground. The distance can be generally measured by a ultra-sonic sensor, but the ultra-sonic sensor has errors according to velocity of a sensor board. To compensate these errors, we proposed a sensor fusion method using a Kalman filter.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.1-8
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• 2020

This paper studied a method of estimating target information using a radar in wireless communication. Position information on the target can be estimated angle, distance and velocity. The velocity information can be estimated since the Doppler frequency is changed in the moving target. The signal incident on the receiving array antenna is multiplied by the delay time and the reference signal to represent the output signal. This output signal is estimated by applying FFT (Fast Fourier Transform) after calculating signal correlation through correlation integrator. Since the output signal must be calculated within the correlator, it should be processed with the Dwell time. The correlation signal of the correlation integrator outside this Dwell time is indicated by the velocity measurement error. The FFT is applied to the signal that has passed through the correlated integrator in order to estimate the distance of the signal. The Doppler resolution must be improved because the FFT estimates target information using the Doppler information. The Doppler resolution decreases with increasing the integration time. The velocity information estimation should have no spread of the velocity. As a result of the simulation, there was no spread of the target velocity in this study.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.261-262
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• 2012

In this research, intelligent protection system for laser boat is introduced. The function of system is to measure the distance and velocity of object from our boat and generate control signals to avoid collision with moving targets. A novel approach to estimate object's position from our ship is tackled on this paper. To do this laser sensors are used to measure distance from ship to targets. The ship position and velocity is estimated by th Kalman filter algorithm. In the real phase, the filtering method will be applied to process signal gathered by laser sensors. Simulation to estimate ship's position and velocity under noise are executed and the results are introduced to show the effectiveness of the algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.104-113
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• 2022

In this paper, we propose deep learning-based target distance and velocity estimation technique for OFDM radar systems. In the proposed technique, the 2D periodogram is obtained via 2D fast Fourier transform (FFT) from the reflected signal after removing the modulation effect. The periodogram is the input to the conventional and proposed estimators. The peak of the 2D periodogram represents the target, and the constant false alarm rate (CFAR) algorithm is the most popular conventional technique for the target's distance and speed estimation. In contrast, the proposed method is designed using the multiple output convolutional neural network (CNN). Unlike the conventional CFAR, the proposed estimator is easier to use because it does not require any additional information such as noise power. According to the simulation results, the proposed CNN improves the mean square error (MSE) by more than 5 times compared with the conventional CFAR, and the proposed estimator becomes more accurate as the number of transmitted OFDM symbols increases.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.519-524
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• 2004

This study is concerned with the braking distance estimation using frictional energy rate. First, steady state rolling analysis is performed, and using this result, the braking distance is estimated. Dynamic rolling analysis during entire braking time period is impratical, so that this study divides the vehicle velocity by 10km/h to reduce the analysis time. The multiplication of the slip rate and the shear stress provides the frictional energy rate. Using frictional energy rate, total braking distance is estimated, In addition, ABS(Anti-lock Brake System) is considered, and two type of slip ratios are compared, One is 15% slip ratio for the ABS condition, and the other is 100% slip ratio which leads lo the almost same braking distance as the elementary kinematic theory. A slip ratio is controlled by angular velocity in ABAQUS/Explicit, A 15% slip ratio gives the real vehicle's braking distance when the frictional energy occurred al disk pad is included. Disk pad's frictional energy rate is calculated by the theoretical approach.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.21-29
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• 2011

This paper presents a method that estimates distance and velocity of an object with reliability regardless of maneuver status of the target in stereo vision system. A stereo vision system can calculate a distance with disparity from left and right images. However, the distance estimation error may occur due to quantization error of image pixel. A sub-pixel interpolation method minimizes the quantization error and estimates accurate disparity with real value. Extended Kalman filter (EKF) was used to minimize the error covariance and estimate the object's velocity. However, divergence problem occurs due to model uncertainty when a target maneuvers highly, which makes the estimation error increase. In this paper, we propose a virtual model extended Kalman filter (VMEKF) method that minimizes the processing time and provides reliable estimation ability regardless of maneuver status. Computer simulations and experimental results in real road environments demonstrate that the proposed method gives a reliable estimation performance and reduces processing time under various maneuver status while comparing other estimation filters.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.625-628
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• 2007

We present an efficient and robust technique to estimate the velocity of moving targets from a single SAR image. In SAR images, azimuth image shift is a well known phenomenon, which is observed in moving targets having slant-range velocity. Most methods estimated the velocity of moving targets from the distance difference between the road and moving targets or between ship and the ship wake. However, the methods could not be always applied to moving targets because it is difficult to find the road and the ship wake. We adopted a method estimating the velocity of moving targets from azimuth differentials of range-compressed image. This method is based on an assumption that Doppler center frequency shift of moving target causes a phase difference in azimuth differential values. The phase difference is linearly distorted by Doppler rate due to the geometry of SAR image. The linear distortion is eliminated from phase removal procedure, and the constant phase difference is estimated. Finally, range velocity estimates for moving targets are retrieved. This technique is tested using an ENVISAT ASAR image in which several unknown ships are presented. The theoretical accuracy of this technique is discussed by SAR simulation. The advantages and disadvantages of this method over the conventional method are also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2891-2898
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• 2015

The new developed long distance transport technology uses the effect of electro-magnetic energy. But it's difficult to estimate the new technology. We monitored the velocity profile and pressure drops in pipes and estimated the technology quantitatively from data analysis. Laboratory test and field test gave us that the effects of electro-magnetic energy changed the flow properties and increased the velocity, especially at the slip layer. When transporting the dredged soil, electro-magnetic field generation reduces the frictional resistances at the slip layer, increases the velocity of flow. Furthermore, it would be possible to transport the dredged materials up to 15km long with one pump station.