针对雷达量测存在漏探测情况下的数据关联与空间配准问题，提出了一种基于期望最大化（EM）算法的联合数据关联与空间配准算法。该算法使用EM算法对空间配准问题中的系统偏差进行估计，采用多维分配算法进行数据关联，通过迭代进行数据关联和空间配准，最终得到收敛的系统偏差估计和关联正确率。仿真实验结果表明：在雷达探测为非全探测时，文中提出的联合数据关联与空间配准算法能够有效地估计系统偏差，有较强的抗噪性和鲁棒性。

Aiming at the data association and spatial registration under radar measurements with missing detection, a joint data association and spatial registration algorithm based on expectation maximization (EM) algorithm was derived. The radar system biases were estimated using EM algorithm, measurement data assciation was done using multidimensional assignment, the convergent system biases and associated matrix are finally obtained by jointly applying data association and spatial registration iteratively. Simulation results show that under the environment that measurements may have missed detection, the algorithm proposed in this paper can estimate the system biases efficiently, showing good robustness and anti noise performance.

TN911.7

国家自然科学基金资助项目