• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.9
• /
• pp.3559-3571
• /
• 2015

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.

• Journal of Korea Society of Industrial Information Systems
• /
• v.21 no.3
• /
• pp.21-28
• /
• 2016

Compressed sensing is a signal processing technique for efficiently acquiring and reconstructing in an under-sampled (i.e., under Nyquist rate) representation. Specially, a block compressed sensing with Smoothed Projected Landweber (BCS-SPL) framework is one of the most widely used schemes. Currently, a variety of BCS-SPL schemes have been actively studied. However, when restoring, block sizes have effects on the reconstructed visual qualities, and in this paper, both a basic scheme of BCS-SPL and several modified schemes of BCS-SPL with structured measurement matrix are analyzed for the effects of the block sizes on the performances of reconstructed image qualities. Through several experiments, it is shown that a basic scheme of BCS-SPL provides superior performance in block size 4.

• ETRI Journal
• /
• v.37 no.6
• /
• pp.1154-1164
• /
• 2015

This paper proposes a fully sensorless driver for a permanent magnet synchronous motor (PMSM) integrated with a digital motor controller and an analog pre-driver, including sensing circuits and estimators. In the motor controller, a position estimator estimates the back electromotive force and rotor position using a sliding-mode observer. In the pre-driver, drivers for the power devices are designed with a level shifter and isolation technique. In addition, a current sensing circuit measures a three-phase current. All of these circuits are integrated in a single chip such that the driver achieves control of the speed with high accuracy. Using an IC fabricated using a $0.18{\mu}m$ BCDMOS process, the performance was verified experimentally. The driver showed stable operation in spite of the variation in speed and load, a similar efficiency near 1% compared to a commercial driver, a low speed error of about 0.1%, and therefore good performance for the PMSM drive.

• Journal of Power Electronics
• /
• v.5 no.3
• /
• pp.173-179
• /
• 2005

In this paper, a very low cost and robust sensing method for the rotor position of a TSRM(Toroidal Switched Reluctance Motors) is described. Position information of the rotor is essential for SRM drives. The rotor position sensor such as an opto-interrupter or high performance encoder is generally used for the estimation of rotor position. However, these discrete position sensors not only add complexity and cost to the system but also tend to reduce the reliability of the drive system. In order to solve these problems, in the proposed method, rotor position detection is achieved using voltage waveforms induced by the time varying flux linkage in the search coils, and then the appropriate phases are excited to drive the SRM. But the search coil's EMF is generated only when the motor rotates. Therefore the rotor position sensing method using squared Euclidean distance at a standstill is also examined. The simulation and experimental results are presented to verify the performance of the proposed method in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.1
• /
• pp.1-11
• /
• 2016

We investigate compressive sensing techniques to estimate sparse channel in Orthogonal Frequency Division Multiplexing(OFDM) systems. In the case of large channel delay spread, compressive sensing may not be applicable because it is affected by length of measurement vectors. In this paper, we increase length of measurement vector adding pilot information to OFDM data block. The increased measurement vector improves probability of finding path delay set and Mean Squared Error(MSE) performance. Simulation results show that signal recovery performance of a proposed scheme is better than conventional schemes.

• Journal of Sensor Science and Technology
• /
• v.29 no.6
• /
• pp.365-368
• /
• 2020

As a green and abundant source of energy, H2 has attracted the attention of researchers for use in different applications. Nevertheless, it is highly flammable, and because of its significantly small size, extreme attention is needed to detect its leakage. In this review, we discuss different effects of noble metals on the H2 gas response and performance of metal oxide-based gas sensors. In this regard, we discuss the effects of noble metals, in combination with metal oxides, on H2 gas detection. The catalytic activity towards H2 gas and the formation of heterojunctions with metal oxides are the main contributions of noble metals to the sensing improvement of H2 gas sensors. Furthermore, in the special case of Pd and somewhat Pt, the formation of PdHx and PtHx also affects the H2 sensing performance. This review paper provides useful information for researchers working in the field of H2 gas detection.

• Korean Journal of Remote Sensing
• /
• v.18 no.3
• /
• pp.147-153
• /
• 2002

The real-time reception and recording of down-link mission data from a satellite requires the highest reliability because the data lost in receiving process cannot be recovered. The data receiving and recording system has moved from a set of dedicated hardware and software components to commercial-off-the-shelf (COTS) components in order to reduce the system cost as well as to upgrade the system easily for handling other satellite data. The use of COTS hardware and middleware components prevents the system developer from correcting or modifying the internal operations of the COTS components, and hence, instant performance degradation of the COTS components which affects the reliable data acquisition must be covered by a software algorithm. This paper introduces the instant performance problem of a COTS data recording device which leads to the data loss in the real-time data reception and recording process. As a result, the requirement of the modification of the conventional data read/write technique is issued. In order to overcome the data loss problem due to the use of COTS components and the conventional software technique, a new algorithm called a software buffering technique is proposed. The experiments show that the application of the proposed technique results in reliable real-time reception and recording of high speed serial data.

• Korean Journal of Remote Sensing
• /
• v.24 no.5
• /
• pp.397-408
• /
• 2008

A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.

• Korean Journal of Remote Sensing
• /
• v.14 no.3
• /
• pp.262-276
• /
• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agenrr of japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy- and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is assumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays very similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.637-639
• /
• 2003

As the number of spectral bands of high spectral resolution data increases, the capability to detect more detailed classes should also increase, and the classification accuracy should increase as well. Often, it is impossible to access enough training pixels for supervise classification. For this reason, the performance of traditional classification methods isn't useful. In this paper, we propose a new model for classification that operates based on decision fusion. In this classifier, learning is performed at two steps. In first step, only training samples are used and in second step, this classifier utilizes semilabeled samples in addition to original training samples. At the beginning of this method, spectral bands are categorized in several small groups. Information of each group is used as a new source and classified. Each of this primary classifier has special characteristics and discriminates the spectral space particularly. With using of the benefits of all primary classifiers, it is made sure that the results of the fused local decisions are accurate enough. In decision fusion center, some rules are used to determine the final class of pixels. This method is applied to real remote sensing data. Results show classification performance is improved, and this method may solve the limitation of training samples in the high dimensional data and the Hughes phenomenon may be mitigated.