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UWB microwave imaging for breast tumor detection based on shrinkage covariance matrix estimation

机译:基于收缩协方差矩阵估计的乳腺肿瘤检测UWB微波成像

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This paper presents a new covariance matrix estimate based on shrinkage method for breast tumor detection application. The parameters of shrinkage covariance matrix are obtained by solving a modified semi-definite programming (SDP) convex problem based on the mean-squared error (MSE) criterion. The reconstructed covariance matrix, using the determined shrinkage parameters, is then used to replace the conventional sample covariance matrix (SCM) in the beamformer. The performance of the resulting beamformer is tested by a 2-D numerical breast analysis model and the simulations show the proposed approach possesses a better target identification capability and improves the signal-to-clutter-noise ratio (SCNR).
机译:本文提出了一种基于乳腺肿瘤检测应用收缩方法的新协方差矩阵估计。通过基于平均平均误差(MSE)标准,通过求解修改的半定编程(SDP)凸面问题来获得收缩协方差矩阵的参数。然后,使用所确定的收缩参数的重建协方差矩阵被用于在波束形成器中替换传统的样本协方差矩阵(SCM)。由2-D数值乳房分析模型测试所得到的波束形成器的性能,并且模拟显示所提出的方法具有更好的目标识别能力并提高信号到杂波噪声比(SCNR)。

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