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Adaptive MIMO radar target parameter estimation with Kronecker-product structured interference covariance matrix

机译:Kronecker积结构干扰协方差矩阵的自适应MIMO雷达目标参数估计

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摘要

Multiple-Input Multiple-Output (MIMO) radar with colocated antennas has an increased target parameter estimation performance, but at the cost of increased computational complexity. This paper first presents the conditions required for the interference covariance matrix (ICM) of colocated MIMO radar to take a special structure, namely a Kronecker product of some sub-ICMs, and then proves that based on this ICM structure, the conventional Minimum Variance Distortionless Response (MVDR) algorithm can be reformulated into a combination of three estimation algorithms all of much smaller scales, such that the computational complexity is decreased significantly. However, this ICM structure can be destroyed by inactive scattering sources, whose influence is studied via numerical experiments. It is found that inactive point scatterers can still be suppressed by adaptive algorithms relying on the ICM structure, on condition that the number is fewer than that of receiving antennas.
机译:具有共置天线的多输入多输出(MIMO)雷达具有增强的目标参数估计性能,但以增加的计算复杂性为代价。本文首先提出了共置MIMO雷达的干扰协方差矩阵(ICM)采用特殊结构即某些子ICM的Kronecker乘积的条件,然后证明了基于此ICM结构的常规最小方差无失真响应(MVDR)算法可以重新组合为三种规模较小的估计算法的组合,从而大大降低了计算复杂度。但是,这种ICM结构可能会被非活动的散射源破坏,并通过数值实验研究了其影响。发现在不超过接收天线数量的情况下,依靠ICM结构的自适应算法仍然可以抑制非活动点散射。

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