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Adaptive polarisation-space-time domain radar target detection in inhomogeneous clutter environments

机译:非均匀杂波环境下的自适应极化时空雷达目标检测

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The polarisation-space-time processing technique performs significantly better than the space-time processing technique, as it makes use of the polarisation information as well as the angle and Doppler information of radar returns when the secondary data set is large enough to overcome the detection loss. However, considering the degree of freedom of the polarisation-spacetime processor, it is rarely possible to obtain such a large set of secondary data vectors, especially in an airborne radar target detection where clutter is inhomogeneous and/or non-stationary. Here, two adaptive polarisation-space-time localised processors, which are of significant use in limited secondary data environments, are developed by efficiently combining the space-time localised processor and the polarisation processor. The authors first analyse the performance potential of the polarisation-space-time processors with different configurations because selecting a processor configuration is a critical issue that should be solved prior to developing adaptive algorithms. The detection performance of the adaptive processors developed by considering the performance potential is then derived analytically in terms of the probabilities of detection and false alarm, and a performance comparison is made for limited secondary data environments.
机译:极化时空处理技术的性能明显优于时空处理技术,因为它利用极化信息以及辅助数据集足够大以克服检测时雷达返回的角度和多普勒信息失利。但是,考虑到极化时空处理器的自由度,很少有可能获得如此大量的辅助数据矢量,尤其是在杂波不均匀和/或不稳定的机载雷达目标检测中。在此,通过有效地组合空时本地化处理器和极化处理器,开发了在有限的辅助数据环境中大量使用的两个自适应极化时空本地化处理器。作者首先分析了具有不同配置的极化时空处理器的性能潜力,因为选择处理器配置是在开发自适应算法之前应解决的关键问题。然后根据检测和虚警的可能性,通过分析得出通过考虑性能潜能而开发的自适应处理器的检测性能,并对有限的辅助数据环境进行性能比较。

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