对于双基地多输入多输出(multiple input multiple output,MIMO)雷达,发射和接收阵列幅相误差耦合到一起,不易单独测量。针对阵列存在小扰动幅相误差的MIMO雷达,分别推导了借助旋转不变信号参数估计技术(estimating signal parameter vi...对于双基地多输入多输出(multiple input multiple output,MIMO)雷达,发射和接收阵列幅相误差耦合到一起,不易单独测量。针对阵列存在小扰动幅相误差的MIMO雷达,分别推导了借助旋转不变信号参数估计技术(estimating signal parameter via rotational invariance techniques,ESPRIT)算法的到达角(direction of ar-rival,DOA)和离开角(direction of departure,DOD)的均方根误差(root mean square error,RMSE)与幅相误差关系表达式。与其他方法相比,ESPRIT算法可以将发射和接收阵列的幅相误差进行解耦,并且DOA和DOD的RMSE只与阵列相位误差相关,与阵列幅值误差无关。仿真结果表明,理论值和仿真实验值能够较好地吻合,验证了理论的正确性。展开更多
Longitudinal data often arise when subjects are followed over a period of time, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-...Longitudinal data often arise when subjects are followed over a period of time, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. In this article, we propose joint modeling and analysis of longitudinal data with possibly informative observation times and a dependent terminal event in which a common subject-specific latent variable is used to characterize the correlations. A borrow-strength estimation procedure is developed for parameter estimation, and both large-sample and finite^sample properties of the proposed estimators are established. In addition, some goodness-of-fit methods for assessing the adequacy of the model are provided. An application to a bladder cancer study is illustrated.展开更多
文摘对于双基地多输入多输出(multiple input multiple output,MIMO)雷达,发射和接收阵列幅相误差耦合到一起,不易单独测量。针对阵列存在小扰动幅相误差的MIMO雷达,分别推导了借助旋转不变信号参数估计技术(estimating signal parameter via rotational invariance techniques,ESPRIT)算法的到达角(direction of ar-rival,DOA)和离开角(direction of departure,DOD)的均方根误差(root mean square error,RMSE)与幅相误差关系表达式。与其他方法相比,ESPRIT算法可以将发射和接收阵列的幅相误差进行解耦,并且DOA和DOD的RMSE只与阵列相位误差相关,与阵列幅值误差无关。仿真结果表明,理论值和仿真实验值能够较好地吻合,验证了理论的正确性。
基金Supported by the National Natural Science Foundation of China Grants(No.11231010 and 11171330)Key Laboratory of RCSDS,CAS(No.2008DP173182)
文摘Longitudinal data often arise when subjects are followed over a period of time, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. In this article, we propose joint modeling and analysis of longitudinal data with possibly informative observation times and a dependent terminal event in which a common subject-specific latent variable is used to characterize the correlations. A borrow-strength estimation procedure is developed for parameter estimation, and both large-sample and finite^sample properties of the proposed estimators are established. In addition, some goodness-of-fit methods for assessing the adequacy of the model are provided. An application to a bladder cancer study is illustrated.
