【摘要】 为了充分利用多入多出(multiple input multipleoutput,MIMO)雷达的空间分集技术,同时使其便于设计和实现,论文基于目标的分布源模型,在Neyman-Pearson准则下研究当MIMO雷达分集路径不完全独立时的检测方法和性能,并且利用主分量分析的思想简化了检测方法。该方法通过特征值分解,从M个正交信号中提取出独立观测分量并将其加权合并。仿真结果表明:与传统雷达相比,只要存在2个以上的独立观测分量,MIMO雷达可以更有效地对抗目标RCS(radar cross section)闪烁。同时,当发射阵元间距减小为理想条件的1/4时,MIMO雷达仍然可以利用空间分集提高其检测性能。更多还原

【Abstract】 The spatial diversity of multiple input multiple output(MIMO) radar was analyzed based on a distributed source model under the Neyman-Pearson criterion when the observation paths were not strictly independent of each other.The detector was then simplified based on the primary component analysis.An eigenvector analysis of the covariance of the received signal vectors was used to extract the independent components of the vectors from M received signals,which were combined by the detector.Simulations show that as long as more than 2 independent components are obtained,the MIMO radar is still able to counter the target’s radar cross section(RCS) scintillation compared with conventional phase radar,even if the observation paths were not entirely independent.In addition,MIMO radar can efficiently detect fading targets using the spatial diversity when the distance between the transmitter elements is decreased to 1/4 that for the ideal conditions.更多还原