Achieving accurate clock synchronization may not be feasible for distributed multiple-input multiple-output (MIMO) radar systems with non-ideal clocks of the sensors. In this paper, the problem of target localization and clock synchronization in distributed MIMO radar systems in presence of time synchronization errors is addressed by utilizing time delay measurements. Firstly, the necessity to consider time synchronization errors when locating a target is illustrated by analyzing the increase in Cramer-Rao lower bound (CRLB) of the target position due to the time synchronization error. Then, a self-synchronized localization framework based on the hybrid maximum likelihood and maximum a posteriori estimator is proposed to estimate the target position and time synchronization error sequentially. Specifically, a method based on the levenberg marquardt algorithm and an analytical solution are developed respectively to estimate the target position, and a combination strategy is recommended further based on the two methods to achieve a more accurate target position estimate. The time synchronization error is figured out then by utilizing the target position estimate. Meanwhile, the closed-form solution of estimating the target position and time synchronization error is analytically proved to be approximately unbiased and can attain the CRLB under weak noise conditions. It is demonstrated through numerical simulations that the combination strategy has better estimation performance than the two methods. Simultaneously, simulation results show that the proposed self-synchronized localization method outperforms the state-of-the-art algorithms in the target position and time synchronization error estimation accuracy.

中文翻译：

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具有时间同步误差的分布式 MIMO 雷达系统中的目标定位和时钟细化


对于传感器时钟非理想的分布式多输入多输出（MIMO）雷达系统来说，实现精确的时钟同步可能不可行。在本文中，通过利用时延测量来解决存在时间同步误差的分布式 MIMO 雷达系统中的目标定位和时钟同步问题。首先，通过分析时间同步误差导致的目标位置克拉默-饶下界（CRLB）的增加，说明定位目标时考虑时间同步误差的必要性。然后，提出了一种基于混合最大似然和最大后验估计器的自同步定位框架来顺序估计目标位置和时间同步误差。具体来说，分别开发了基于levenberg marquardt算法和解析解的方法来估计目标位置，并进一步基于两种方法推荐组合策略，以实现更准确的目标位置估计。然后利用目标位置估计来计算出时间同步误差。同时，分析证明估计目标位置和时间同步误差的闭式解是近似无偏的，并且可以在弱噪声条件下获得CRLB。通过数值模拟表明，该组合策略比两种方法具有更好的估计性能。同时，仿真结果表明，所提出的自同步定位方法在目标位置和时间同步误差估计精度方面优于最先进的算法。