基于概率定义扩展样本的机载雷达空间和时间相关海杂波数据仿真方法

海杂波背景下的目标检测性能是机载预警雷达的重要指标之一。为了给机载雷达海杂波抑制方案的有效设计提供数据来源，需要仿真模拟出满足实际分布特性和相关性的海杂波。针对实测海杂波数据具有的显著时间相关性和空间相关性，提出了一种新的海杂波数据产生方法。该方法基于概率密度定义及相关性的本质，运用蒙特卡罗思想和Cholesky分解来产生空间和时间相关的海杂波。这种方法不仅简化了海杂波数据产生流程，同时提高了海杂波幅度和相关性吻合效果。分别利用实测和仿真数据验证了所提方法的有效性。

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

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.