Application of Road Information in Ground Moving Target Tracking

A new algorithm is developed to achieve accurate state estimation in ground moving target tracking by means of using road information. It is an adaptive variable structure interacting multiple model estimator with dynamic models modification （DMM VS-IMM for short）. Firstly, road information is employed to modify the target dynamic models used by filter, including modification of state transition matrix and process noise. Secondly, road information is applied to update the model set of a VS-IMM estimator. Predicted state estimation and road information are used to locate the target in the road network on which the model set is updated and finally IMM filtering is implemented. As compared with traditional methods, the accuracy of state estimation is improved for target moving not only on a single road, but also through an intersection. Monte Carlo simulation demonstrates the efficiency and robustness of the proposed algorithm with moderate computational loads.

地理信息辅助地面目标跟踪算法研究

不断变化的地理地形信息不仅能够限制目标的运动性能,而且能够降低测量数据的质量。但是地理信息的合理开发与利用则能够在很大程度上提高地面目标的跟踪性能。为了研究地理信息对地面目标跟踪性能提高的算法,基于现有的研究成果,对其进行分类研究,并对基于VS-IMM(Variable Structure Interacting Multiple Model)的跟踪算法进行了梳理。详细地分析地理信息如何辅助该算法,以提高航迹的质量和连续性。最后,对地理信息辅助地面目标跟踪算法进行了总结与对比性分析,对利用人工智能算法跟踪地面目标进行展望。

基于地理信息的地面运动目标跟踪方法

为了提高地面运动目标跟踪精度,提出了基于地理信息约束的变结构交互多模(VS-IMM)的目标跟踪算法。通过建立地理信息系统约束地面目标运动状态,并利用目标转弯曲线模型确定滤波器中机动目标的时变运动模型集,采用地理信息约束的变结构交互多模算法可更符合实际进行地面目标机动跟踪。针对机场地面机动目标的仿真结果表明,给出的地理条件约束的目标跟踪算法比现有交互多模算法具有更好的性能。