中文摘要：

针对混合网格变结构多模型算法中用于描述目标运动模式的加速度估计不准确引起跟踪精度下降的问题,本文提出了一种基于“当前”统计模型（Current Statistics,CS）的混合网格多模型算法（Hybrid Grid Multiple Model,HGMM）。该算法以基于“当前”统计模型估计得到的加速度均值为依据进行网格划分,在线生成目标可能的模型集合,采用交互式多模型算法进行目标跟踪。在一般机动及强机动场景下进行了算法性能测试分析,仿真结果表明,该算法提高了对机动目标的跟踪精度。

英文摘要：

Due to decline problem of tracking accuracy caused by acceleration estimation inaccuracy in Hybrid Grid Multiple Model （HGMM） algorithm, a new HGMM algorithm based on Current Statistics （CS） model is proposed, since the current acceleration mean in CS model can reflect true target motion model more accurately. Grid partition is performed by estimation of the acceleration mean in CS model, and possible model set of the target is generated online. Then, interactive multiple model algorithm is adopted to track target. The proposed algorithm performance is tested and compared in general and strong maneuvering scenarios, and simulation results demonstrate that the proposed algorithm not only improves the accuracy for maneuvering target tracking, but also can be applied to most of the tracking scenarios.