杂波环境密集机动目标跟踪PCIMM-UKF算法

杂波环境密集机动目标跟踪对于数据关联和滤波始终是一个挑战性问题，本文提出的PC（投影收缩）IMM（交互多模型）-UKF（无迹卡尔曼滤波）算法，利用优化领域前沿研究成果之一的投影收缩算法，解决了全局最优关联问题，同时将IMM和UKF算法结合，克服了非线性机动目标跟踪困难的缺点，大量数值仿真结果也表明该算法可行且有效。

Tracking Closely Spaced Maneuvering Targets in Clutter with PCIMM-UKF Algorithm

Tracking closely spaced maneuvering targets in clutter is a great challenge for both the contact-to-track association and the position estimation algorithms. In this paper, we propose a PCIMM-UKF algorithm, which utilizes Projection and Contraction （PC） method, one of achievements in optimization field, for the global optimal association. At the same time we combine IMM method with UKF for nonlinear maneuvering target tracking. As demonstrated by numerous numerical simulations, the proposed method is both effective and efficient.