• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1803-1813
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• 1996

This paper describes an automatic threshold decision using a maximum mismatched correlation value in the direct sequence spread spectrum (DS-SS) system. For received PN codes with different single-to-noise ratio (SNR), this scheme is able to detect a desired threshold value in the search mode, i.e. a maximum mismstched correlation value, so that value is utilized as a threshold for the verification mode. Performance of the proposed scheme in both the additive white gaussian noise (AWGN) and frequency-selective Rayleigh fading channels is analyzed through the Monte Carlo simulation. And hardware implementation of this scheme using a DSP processor is demonstrated. The proposed acquisition shceme is compared to the conventional constant threshold (CT) scheme, and significant improvement of performance is shown. Analysis of system performance in the verification mode is presented, and key quantities such as the false alarm probability and the detection probability are derived in a AWGN channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4797-4813
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• 2018

The transform domain communication system (Hereinafter referred to as TDCS) takes on numerous advantages, inclusive of anti-jamming and low probability of detection. Yet its application is confined by the consistent spectrum in the transmitter and receiver, which is not possible in the case of a huge distance exsits between them. In this paper, a TDCS based modified weighted fractional fourier transform (WFRFT) is proposed to solve the problem resulting from spectrum mismatching for TDCS application. The amplitude and phase information are incorporated with the TDCS signals and transmit to the receiver together in the wake of a modified WFRFT. The basic function and the TDCS signals shall be accessible to the receivers in the wake of an inverse WFRFT transform, which make sure that the original information can be demodulated properly. The system's reliability while transmitting signals with different modulation methods and with spectrum mismatching is demonstrated by bit error rate (BER). In the meantime, the constellations of the signals and the BER performances at the eavesdropper demonstrate the proposed system is better secured.

• Korean Journal of Optics and Photonics
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• v.1 no.1
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• pp.22-27
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• 1990

The cavity-length detuning characteristics of the hybridly mode-locked dye laser have been studied with a collinear autocorrelator. In the optimum condition, the pulse width is 0.65 ps about three times as short as that of the synchronously mode-locked dye laser. As the cavity length is increased, the pulse width becomes broader than that at the optimum cavity length because of the effect of spontaneous emission. Also, the spectrum width becomes broad, therefore the time bandwidth product ($\Deltat\Deltav$) is increased. The peak power of autocorrelation is maximum at $\Deltat=5.0\umm$ longer than the optimum cavity length. On the other hand, as the cavity length is decreased, the pulse width becomes broader and the satellite pulses appear because of the gain recovery. Also the spectrum width becomes narrower than that at the optimum cavity length. In particular, at the mismatched cavity length the center of the lasing spectrum moves to shorter wavelengths. ngths.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1041-1051
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• 2014

In this paper, we propose a new image alignment technique based on CUDA SURF in order to solve the initial image alignment problem that frequently occurs in machine vision applications. Machine vision systems using multi-spectral images have recently become more common for solving various decision problems that cannot be performed by the human vision system. These machine vision systems mostly use markers for the initial image alignment. However, there are some applications where the markers cannot be used and the alignment techniques have to be changed whenever their markers are changed. In order to solve these problems, we propose a new image alignment method for multi-spectral machine vision applications based on SURF extracting image features without depending on markers. In this paper, we propose an image alignment method that obtains a sufficient number of feature points from multi-spectral images using SURF and removes outlier iteratively based on a least squares method. We further propose an effective preliminary scheme for removing mismatched feature point pairs that may affect the overall performance of the alignment. In addition, we reduce the execution time by implementing the proposed method using CUDA based on GPGPU in order to guarantee real-time operation. Simulation results show that the proposed method is able to align images effectively in applications where markers cannot be used.