本文针对分布式MIMO雷达系统,在站间大间隔配置获得的空间分集增益的基础上,提出了一种目标位置估计与检测的联合算法.与以往距离门检测不同的是,这里通过所定义的目标假设框架下进行联合估计与检测.通过理论分析证明,本文所提出的位置估计与检测联合算法在检测性能上要优于距离门检测法,且漏检概率与信噪比SNR成反比.仿真实验也验证了算法的有效性.%We consider multiple-input multiple-output (MIMO) radar systems with widely spaced antennas,which facilitate capturing the inherent diversity gain for joint detection and estimation.Unlike conventional MIMO radars that break the space into small cells and aim at detecting the presence of a target in a specified cell,a new MIMO radar framework for detecting a target that lies in an unknown location has been put forward in this paper.We treat this problem through offering a novel composite hypothesis testing framework for target detection.The test offered optimizes a metric that accounts for both detection and estimation accuracies.The analytical and empirical results show that the proposed algorithm is better than classical detection method in MIMO radar.
展开▼