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Adaptive Clutter Nulling Approach for Heterogeneous Environments

机译:异构环境的自适应杂波调零方法

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摘要

Radar processors may suffer from performance loss when the heavy clutter is not sufficiently suppressed in a heterogeneous environment. In order to achieve the clutter suppression and further improve the detection performance, the clutter nulling method is widely addressed in radar systems, especially for the low-rank clutter in space-time adaptive processing, where the rank of the clutter covariance matrix is smaller than the length of test data vector. For the ubiquitous clutter-plus-noise environment in practice, where it is assumed as the superposition of the white Gaussian noise and the low-rank compound-Gaussian clutter without the accurately prior information of the texture, this paper develops a clutter nulling approach, whose kernel and emphasis are to obtain the maximum-likelihood estimation of the orthonormal basis vectors of the clutter subspace. Precisely in processing, the proposed clutter nulling method is mainly derived with the application of the Lagrange multiplier method and adaptively implemented using iteration method with the training data. Finally, the results on numerical data validate the advantages of the proposed nulling approach, in comparison with the existing method.
机译:当在异构环境中无法充分抑制杂波时,雷达处理器可能会遭受性能损失。为了实现杂波抑制并进一步提高检测性能,杂波归零方法在雷达系统中得到了广泛解决,特别是对于空时自适应处理中的低秩杂波,杂波协方差矩阵的秩小于测试数据向量的长度。对于实践中普遍存在的杂波加噪环境,在没有准确的纹理先验信息的情况下,将其假定为白高斯噪声和低阶复合高斯杂波的叠加,本文提出了杂波归零方法,其核心和重点是获得杂波子空间的正交法向量的最大似然估计。精确地在处理中,所提出的杂波归零方法主要是通过拉格朗日乘数法的应用推导而来的,并使用迭代方法对训练数据进行自适应实现。最后,与现有方法相比,数值数据结果验证了所提出的归零方法的优点。

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