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多输入多输出(MIMO)雷达使用多个天线同时发射多个独立探测信号,并使用多个天线接收目标回波信号.本文考虑了发射空域分集、相干接收MIMO雷达模型及其最大似然(ML)参数估计方法.基于最大似然准则,本文推导了两种渐近最大似然算法.仿真实验的结果表明,在均匀噪声模型中,其中一种渐近算法与基于延迟求和波束形成的最大似然算法性能接近,而另一种渐近算法性能略差,但具有较低的计算复杂度.而在非均匀噪声模型中,本文所提出的两种渐近最大似然算法的性能均优于基于延迟求和波束形成的最大似然算法.
Multiple-input multiple-output (MIMO) radar uses multiple antennas to transmit multiple independent detection signals at the same time and uses multiple antennas to receive the target echo signals.This paper considers the transmit spatial diversity, coherent reception MIMO radar model and its maximum likelihood (ML ) Based on the maximum likelihood criterion, two kinds of asymptotic maximum likelihood algorithms are derived in this paper.The simulation results show that in the uniform noise model, one of the asymptotic algorithms and the maximum delay-based beamforming algorithm The performance of the likelihood algorithm is similar, but the performance of the other asymptotic algorithm is slightly worse, but it has a lower computational complexity. However, in the non-uniform noise model, the proposed two kinds of asymptotic maximum likelihood algorithms Maximum likelihood algorithm based on delayed summation beamforming.