A Single-Platform Multi-Sensor Ground Target Tracking Algorithm

Mengyao Wu, Yong-Ting Wang
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Abstract

For improving the platform tracking performance, the ground target tracking fusion based on platform-level multi-source heterogeneous sensors was studied. The association of the target’s state information was built using gray algorithms, and then the results were further tested by the recognition confidence of target type using evidence theory. Additionally, with assistance of road information, the ground target tracking model sets and filter are designed for the tracking. The effectiveness of the algorithm was verified by simulation.
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一种单平台多传感器地面目标跟踪算法
为提高平台跟踪性能,研究了基于平台级多源异构传感器的地面目标跟踪融合。利用灰色算法建立目标状态信息的关联,然后利用证据理论对目标类型的识别置信度对结果进行进一步检验。此外,在道路信息的辅助下,设计了地面目标跟踪模型集和滤波器进行跟踪。通过仿真验证了该算法的有效性。
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