• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.3
• /
• pp.445-450
• /
• 2015

In the moving target problem, the velocity information of the moving target is very important as well as the high accuracy position information. To solve this problem, active researches are being conducted recently with combine the Time Difference of Arrival (TDOA) and Frequency Delay of Arrival(FDOA) measurements. However, since the FDOA measurement is utilizing the Doppler effect due to the relative velocity between the target source and the receiver sensor, it may be difficult to use the FDOA measurement if the moving target speed is not sufficiently fast. In this paper, we propose a method for estimating the position and the velocities of the target by using only the TDOA measurements for the low speed moving target in the indoor environment with sensor network. First, the target position and heading angle are obtained from the estimated positions of two attached transmitters on the target. Then, the target angular and linear velocities are also estimated. In addtion, we apply the Instrumental Variable (IV) technique to compensate the estimation error of the estimated target velocity. In simulation, the performance of the proposed algorithm is verified.

• Annals of Clinical Neurophysiology
• /
• v.1 no.2
• /
• pp.173-181
• /
• 1999

Eye movements serve vision by placing the image of an object on the fovea of each retina, and by preventing slippage of images on the retina. The brain employs two modes of ocular motor control, fast eye movements (saccades) and smooth eye movements. Saccades bring the fovea to a target, and smooth eye movements prevent retinal image slip. Smooth eye movements comprise smooth pursuit, the optokinetic reflex, the vestibulo-ocular reflex (VOR), vergence, and fixation. Saccades achieve rapid refixation of targets that fall on the extrafoveal retina by moving the eyes at peak velocities that can exceed $700^{\circ}/s$. Various brain lesions can affect saccadic latency, velocity, or accuracy. Smooth pursuit maintains fixation of a slowly moving target. The pursuit system responds to slippage of an image near the fovea in order to accelerate the eyes to a velocity that matches that of the target. When smooth eye movements velocity fails to match target velocity, catch-up saccades are used to compensate for limited smooth pursuit velocities. The VOR subserves vision by generating conjugate eye movements that are equal and opposite to head movements. If the VOR gain (the ratio of eye velocity to head velocity) is too high or too low, the target image is off the fovea, and head motion causes oscillopsia, an illusory to-and-fro movement of the environment.

• Korean Journal of Remote Sensing
• /
• v.26 no.3
• /
• pp.297-304
• /
• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Journal of Auto-vehicle Safety Association
• /
• v.9 no.3
• /
• pp.7-12
• /
• 2017

The whiplash is the most important issue of low speed rear-impact. So auto makers are committed to developing a seat to improve whiplash injury. Most NCAP tests have been used by same pulse (Mid Velocity 16kph). Only Euro NCAP uses different pulse that consists of Low, Mid, High velocity. But Euro NCAP also uses same pulse in Mid velocity as other NCAP test. That Mid velocity NCAP pulse was made by rear impact that has 90's vehicle structure properties. That pulse was used until now days. However these days, auto maker use more high tensile steel than 90's as customer and society demand more fuel efficiency and light vehicle with good safety structure. So modern vehicles have different pulse patterns of rear impact than NCAP pulse and 90's vehicle crash properties. In this paper, the test was conducted by following condition. Target car was impacted by the rigid barrier with certain velocity. Finally target vehicle gained delta V 16kph which was same velocity as NCAP Mid Velocity pulse. It is critical velocity which occur long period neck injury. It is very different pulse that was gained by real car impact from NCAP pulse. And it has higher peak G with high fluctuation and short duration than NCAP pulse.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.3
• /
• pp.307-316
• /
• 2016

A multiple radar system is comprised of early warning radar for fast detection of a target and air defense radar for precision intercept. For this reason, target take-over process is required between the two radars. The target take-over should be performed at an appropriate time by consideration of stable tracking and effective fire control. In this paper, operation characteristics of multiple radar system are analyzed and target take-over time determination method using estimation of target tracking performance is proposed for high-velocity targets. The proposed method is validated with ballistic target defense scenarios in the developed integrated simulator.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.29 no.5
• /
• pp.519-525
• /
• 2011

High-resolution earth-observing satellites acquire substantial amount of geospatial images. In addition to high image quality, high-resolution satellite images (HRSI) provide unprecedented direct georegistration accuracy, which have been enabled by accurate orbit determination technology. Direct georegistration is carried out by relating the determined position and attitude of camera to the ground target, i.e., projecting an image point to the earth ellipsoid using the collinearity equation. However, the apparent position of ground target is displaced due to the atmosphere and satellite velocity causing significant georegistration bias. In other words, optic ray from the earth surface to satellite cameras at 400~900km altitude refracts due to the thick atmosphere which is called atmospheric refraction. Velocity aberration is caused by high traveling speed of earth-observing satellites, approximately 7.7 km/s, relative to the earth surface. These effects should be compensated for accurate direct georegistration of HRSI. Therefore, this study presents the equation and the compensation procedure of atmospheric refraction and velocity aberration. Then, the effects are simulated at different image acquisition geometry to present how much bias is introduced. Finally, these effects are evaluated for Quickbird and WorldView-1 based on the physical sensor model.

• Journal of IKEEE
• /
• v.22 no.2
• /
• pp.309-315
• /
• 2018

A Stepped Frequency Radar(SFR) is a method of achieving high range resolution by gradually increasing the frequency of a transmitted pulse to create a wide synthetic bandwidth. However, in the case of moving target, accurate range estimation can not be performed due to the range-Doppler coupling phenomenon, so it is necessary to compensate through accurate velocity estimation. In this paper, we propose a stepped frequency radar waveform with a Coherent Pulse Train(CPT), velocity estimation results according to parameters using this method and VMD(Velocity Measurement Data) were compared and analyzed by numerical simulations.

• Journal of Navigation and Port Research
• /
• v.41 no.5
• /
• pp.297-302
• /
• 2017

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.3
• /
• pp.315-321
• /
• 2023

In this paper, we propose an algorithm that jointly estimates the location and velocity of a near-field moving target in a pulse radar system. The proposed algorithm estimates the location and velocity corresponding to the outcome of orthogonal matching pursuit (OMP) in a 4-dimensional (4D) location-velocity space. To address the high computational complexity of 4D parameter joint estimation, we propose an algorithm that iteratively estimates the target's 2D location and velocity sequentially. Through simulations, we analyze the estimation performance and verify the computational efficiency of the proposed algorithm.