• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.3
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• pp.317-325
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• 2015

In an interference environment, adaptive sidelobe blanking(adaptive SLB: ASB) algorithm effectively cancels the high-duty cycle jammer and blocks the sidelobe signals without the auxiliary antenna. The adaptive SLB for the linearly constrained minimum variance (LCMV) is proposed in this paper. In the proposed scheme, the interference covariance matrix is modified to satisfy the direction constraints of LCMV and the normalized output can be obtained to block sidelobe signals. As the LCMV can be represented as a generalized sidelobe canceller(GSC) form, which is the general framework of various adaptive beamforming(ABF) algorithms, the proposed adaptive SLB can be applied to various ABF methods. The performance of the proposed method is verified through simulation and analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1242-1249
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• 2017

In this paper, we propose a new algorithm for the performance analysis of the sidelobe blanker (SLB) in radar system, which is based on the matrix pencil method (MPM). In general, the SLB in radar is composed of the main antenna, the auxiliary antenna, and the processing unit. The auxiliary antenna with wide beamwidth receives interference signals such as jamming or clutter signals. The main antenna with high gain receives the target signal in the main beam and the interference signals in the sidelobe. In this paper the Swerling model is used as the target echo signal by considering a probabilistic radar cross section (RCS) of the target. To estimate the SLB performance it needs to calculate the probability of target detection and the probability of blanking the interference by using the signals received from the main and auxiliary antennas. The detection probability and the blanking probability include multiple summations of infinite series with infinite integrations, of which convergence rate is very slow. Increase of summation range to improve the calculation accuracy may lead to an overflow error in computer simulations. In this paper, to resolve the above problems, we used the MPM to calculate a summation of infinite series and improved the calculation accuracy and the convergence rate.