A Method Based on Probability Definition with Extended Samples to Generate Spatial-temporal Correlated Sea Clutter forAirborne Radar

doi:10.3969/j.issn.1000-1093.2019.03.011

Abstract

Abstract: Target detection performance in the background of sea clutter is one of the important indicators of airborne early-warning radar. The sea clutter with actual distribution characteristics and correlation are simulated to provide data sources for the effective design of airborne radar sea clutter suppression schemes. For the significant temporal correlation and spatial correlation of measured sea clutter data, a new method is proposed for generating sea clutter data. The proposed method is based on the definition of probability density and the nature of correlation. Monte Carlo method and Cholesky decomposition are used to generate spatial-temporal correlated sea clutter. The proposed method can be used to simplify the generation process of sea clutter data and improve the amplitude and correlation of sea clutter. The effectiveness of the proposed method is verified by using the measured and simulated data. Key

Key words: airborneradar, seaclutter, datasimulation, spatial-temporalcorrelation, measureddata

CLC Number:

TN959.73

MAO Huihuang, XIE Wenchong, XU Peng, LIU Chang. A Method Based on Probability Definition with Extended Samples to Generate Spatial-temporal Correlated Sea Clutter forAirborne Radar[J]. Acta Armamentarii, 2019, 40(3): 530-538.

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第40卷第3期2019 年3月兵工学报ACTA
ARMAMENTARIIVol.40No.3Mar.2019

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