• Journal of Digital Convergence
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• v.19 no.12
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• pp.339-345
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• 2021

In this paper, estimation angle performance analysis of amplitude-comparison monopulse radar under additive noise effect is dealt with. When uncorrelated white noises are added to the squinted beams, the angle estimation performance is analyzed through the mean square error(MSE). The numerical integration-based mean square error result completely overlaps the Monte Carlo-based mean square error result, which corresponds to 99.8% of the Monte Carlo-based mean square error result. In addition, the mean square error analysis method based on numerical integration has a much faster operation time than the mean square error method based on Monte Carlo. the angle estimation performance of the amplitude comparison monopulse radar can be efficiently analyzed in various noise environments through the proposed numerical integration-based mean square error method.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.43-50
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• 2022

In this paper, it is shown how the performance of the monopulse algorithm in additive noise is evaluated. In the previous study, the performance analysis of the amplitude-comparison monopulse algorithm was conducted via the first-order and second-order Taylor expansion of four variables. By defining two new random variables from the four variables, it is shown that computational complexity associated with two random variables is much smaller than that associated with four random variables. Performance in terms of mean square error is analyzed from Monte-Carlo simulation. The scheme proposed in this paper is more efficient than that suggested in the previous study in terms of computational complexity. The expressions derived in this study can be utilized in getting analytic expressions of the mean square errors.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.14-21
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• 2021

In this paper, it is shown how the performance of the monopulse algorithm in the presence of an additive noise can be obtained analytically. In the previous study, analytic performance analysis based on the first-order Taylor series and the second-order Taylor series has been conducted. By adopting the third-order Taylor series, it is shown that the analytic performance based on the third-order Taylor series can be made closer to the performance of the original monopulse algorithm than the analytic performance based on the first-order Taylor series and the second-order Taylor series. The analytic MSE based on the third-order Taylor approximation reduces the analytic MSE error based on the second-order Taylor approximation by 89.5%. It also shows faster results in all cases than the Monte Carlo-based MSE. Through this study, it is possible to explicitly analyze the angle estimation ability of monopulse radar in an environment where noise jamming is applied.