• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.63-70
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• 2008

This paper presents a method of PRI do-interleaving for LASER pulse signals. When the PRI of LASER pulse is periodically changed, the first deviation and the second deviation of TOA is used to calculate the PRI pattern of input LASER signals of receiver. If the standard deviation of the first difference of TOA is less than 5% of the average of the first difference of TOA, the PRI pattern of LASER signal is fixed or jittered type. If the standard deviation is larger than 5% of the average, those are triangular PRI patterns or sawtooth PRI patterns.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5372-5378
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• 2012

In this paper, we propose a new method to quickly deinterleave the stagger PRI signals and D&S(Dwell and Switch) PRI signals from the EP radar using the electronic warfare system. While former algorithms were based on stochastic methods only using the first deviation of the TOA of radar signals, this paper uses the first and the second deviation of the TOA of radar signals to deinterleave multiple PRIs of EP radars. When we simulate multiple PRIs of EP radars and test the simulated radar signals using the proposed algorithm, various PRI signals such as fixed, jitter, D&S and stagger PRI are well deinterleaved in a short time. This algorithm is found to be very useful for electronic warfare systems.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.137-143
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• 2018

Generally, a radar signal is modulated and transmitted in order to avoid signal detection. In electronic warfare, the specification of a radar is recognized by analysing the received radar pulses. In this paper, we propose an algorithm to recognize the PRI (Pulse Repetition Interval) type of radar signals. This algorithm uses the autocorrelation technique applying different comparison ranges according to the PRI type. It applies a short comparison window to stable and staggered PRI, and a relatively large comparison range to jittered PRI. The experiment shows that the proposed algorithm can discriminate the PRI type of radar pulses correctly. For the more, it can find out the stagger level of staggered type of radar signals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1832-1838
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• 2009

In this paper, we present new signal de-interleaving method for the frequency agility radar in which the carrier frequency is changed irregularly. Generally radar use a fixed carrier frequency, and it is easy for electronic warfare system to de-interleave the radar signal with respect to the frequency, pulse width(PW), and direction of signal arriving(DOA). In frequency agility radar, it is difficult to de-interleave the radar signals according to the carrier frequency because the frequency is changed irregularly. We suggest a good de-interleaving method to identify the frequency agility radar signals in comparison with PRI's of radars. First we calculate pulse repeat Interval(PRI) of radar in linked-list and queue structure and de-interleave the radar signals with PRI, PW, and DOA, then identify the frequency agility radar. When we use the proposed algorism to the frequency agility radar, we have a good de-interleaving results with electronic warfare systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1536-1541
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• 2009

In this paper, we present a novel pulse train identification method for two step stagger pulse train. Generally radar uses a fixed pulse train, and it is easy for electronic warfare system to measure the pulse repeat interval(PRI) and identify the radar. But it is very difficult to measure the PRI of stagger pulse radar because the pulse interval is periodically changed. We suggest a novel method to measure the PRI and identify the radars using the second deviation of pulse train. This method is faster comparing with Histogram method. We have a good PRI measurement results for 2 step stagger signals.

• Design & Manufacturing
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• v.11 no.2
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• pp.1-8
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• 2017

In this study, we applied microcellular foaming injection molding process to improve the performance of system air-conditioner drain fan which had been produced by injection molding process and studied the optimization of process conditions through 6-sigma process and response surface method (RSM) to reduce weight and deformation of products. Additive type, melt temperature, mold temperature, and injection screw shape were selected as the factor affecting the weight and deformation of the products by carrying out analysis of trivial many through ANOVA and design of experiment (DOE) method. Among the effect factor, we set the addictive type to Long G/F and screw shape to foaming screw which had the highest level of weight reduction and deformation reduction. The amount of foaming agent gas was set at 60 ml, which was the limit beyond which the weight of product did not decrease any more. For melt temperature and mold temperature, we studied the conditions where both weight and deformation were minimized using the RSM. As a result, we set the melt temperature to $250^{\circ}C$, fixed mold temperature to $20^{\circ}C$, and moving mold temperature to $40^{\circ}C$. The improvement effect was analyzed by appling the selected optimal conditions to the production process using the microcellular foaming injection molding. The results showed that the mean weight of product was measured to be 1,420g which was 19% lower than that measured in the current process. The standard deviations of the weights were found to be similar to those in the current process and it showed a low dispersion. The mean deformation was measured to be 0.9237mm, which represented a 57% reduction compared to the mean deformation in the current process, and the standard deviation decreased from 0.3298mm to 0.1398mm. Moreover, we analyzed the process capability for deformation, and the results showed that the short-term process capability increased from 2.73 to 6.60 which was even higher than targeted level of 6.0.