• Transactions of the Korean Society of Automotive Engineers
• /
• v.23 no.4
• /
• pp.380-387
• /
• 2015

Various forms of passive shock absorber have developed to supplement performance which is poorer than that of active shock absorber. It is called 'Hybrid Conventional Damper (HCD)'. Frequency sensing shock absorber that this study will cover belongs to the HCD. This study aims to demonstrate that performance of frequency sensing shock absorber is superior than that of passive shock absorber. Study process is as follows. Firstly, analysis models for both passive shock absorber and frequency sensing shock absorber are developed to secure reliability. Then, elements which cause difference of ride quality are found out through comparison of hysteresis characteristics. By comparison of frequency characteristic, furthermore, damping principle of frequency sensing shock absorber is understood. Also, it determines if the absorber performs well even though maximum excitation speed is changed. Finally, the study proves that performance of frequency sensing shock absorber is superior than that of passive shock absorber after comparing change of damping power in excitation condition that various frequencies are mixed.

• Journal of the Optical Society of Korea
• /
• v.15 no.4
• /
• pp.357-361
• /
• 2011

Photon-counting sensing is a widely used technique for low-light-level imaging applications. This paper proposes a distance information extraction method with photon-counting passive sensing under low-lightlevel conditions. The photo-counting passive sensing combined with integral imaging generates a photon-limited elemental image array. Maximum-likelihood estimation (MLE) is used to reconstruct the photon-limited image at certain depth levels. The distance information is extracted at the depth level that minimizes the sum of the standard deviation of the corresponding photo-events in the elemental image array. Experimental and simulation results confirm that the proposed method can extract the distance information of the object under low-light-level conditions.

• ETRI Journal
• /
• v.31 no.3
• /
• pp.348-350
• /
• 2009

To fit the limited volume and power consumption of the passive radio frequency transmission system of the electronic time fuze, an improved coded mark inversion (CMI) is proposed in this letter. From the performance analysis, the energy transmission efficiency of this encoding method is at least 50% higher than that of CMI and NRZ. Finally, the experiment results show that by adopting this improved CMI, the change of DC voltage through magnetic coupling is lower than 0.2 V when the accuracy of data transmission is above 99.5%.

• Korean Journal of Optics and Photonics
• /
• v.17 no.5
• /
• pp.391-395
• /
• 2006

In this paper, radiometric calibration of a FTIR spectrometer for passive remote sensing application was introduced and verified. Radiometric calibration is a significant signal processing procedure to retrieve the object radiance from the measured spectrum. The object radiance is measured and registered distorted by the detector's responsivity dependent on wavelength and instrument self-emission. Radiance of two temperature points, hot temperature and cold temperature, from a well-controlled blackbody was measured and used to obtain the scale factor and offset factor which are required for radiometric calibration. For gas phase C2H5OH. radiometric calibration was done and verified through comparison of its emission line width and intensity with the standard spectrum.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.142-145
• /
• 2006

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the NOAA HWind wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.3
• /
• pp.11-17
• /
• 2019

In this paper, we propose a method to recognize the moving direction in the indoor environment by using the sensing system equipped with passive infrared (PIR) sensors and a deep learning algorithm. A PIR sensor generates a signal that can be distinguished according to the direction of movement of the user. A sensing system with four PIR sensors deployed by $45^{\circ}$ increments is developed and installed in the ceiling of the room. The PIR sensor signals from 6 users with 10-time experiments for 8 directions were collected. We extracted the raw data sets and performed experiments varying the number of sensors fed into the deep learning algorithm. The proposed sensing system using deep learning algorithm can recognize the users' moving direction by 99.2 %. In addition, with only one PIR senor, the recognition accuracy reaches 98.4%.

• Journal of Ocean Engineering and Technology
• /
• v.34 no.3
• /
• pp.227-236
• /
• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• Korean Journal of Remote Sensing
• /
• v.20 no.1
• /
• pp.47-55
• /
• 2004

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced by global data centers, to our knowledge, this is the first attempt to process 10-minute long direct-broadcast (DB) data. We found that the processor designed for a granule needs modification to apply to the DB data. The modification includes the correction to path number, the selection of land mask and the manipulation of dummy scans. Pixel-to-pixel comparison with a reference indicates the difference in brightness temperature of about 0.2 K rms and less than 0.05 K mean. The difference comes from the different length of data between 50-minute granule and about 10-minute DB data. In detail, due to the short data length, DB data do not always have correct cold sky mirror count. The DB processing system is automated to enable the near-real time generation of brightness temperatures within 5 minutes after downlink. Through this work, we would be able to enhance the use of AMSR-E data, thus serving the objective of direct-broadcast.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.319-322
• /
• 1999

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.

• Smart Structures and Systems
• /
• v.4 no.5
• /
• pp.531-548
• /
• 2008

Recently, dense sensor instrumentation for structural health monitoring has motivated the need for novel passive wireless sensors that do not require a portable power source, such as batteries. Using a layer-by-layer self-assembly process, nano-structured multifunctional carbon nanotube-based thin film sensors of controlled morphology are fabricated. Through judicious selection of polyelectrolytic constituents, specific sensing transduction mechanisms can be encoded within these homogenous thin films. In this study, the thin films are specifically designed to change electrical properties to strain and pH stimulus. Validation of wireless communications is performed using traditional magnetic coil antennas of various turns for passive RFID (radio frequency identification) applications. Preliminary experimental results shown in this study have identified characteristic frequency and bandwidth changes in tandem with varying strain and pH, respectively. Finally, ongoing research is presented on the use of gold nanocolloids and carbon nanotubes during layer-by-layer assembly to fabricate highly conductive coil antennas for wireless communications.