改进的联合概率数据关联算法（JPDA）对红外目标与诱饵的辨别

红外诱饵干扰作为常见的影响红外跟踪能力的干扰手段发展的越来越先进，如何有效的排除红外诱饵的干扰一直是红外目标跟踪的难题。文中在研究了红外目标与诱饵干扰的特征差异的基础上，首次提出了将多目标跟踪策略应用于红外抗干扰跟踪中，建立了一种可以融合多个特征的改进型联合概率数据关联（JPDA）的数据关联算法。最后，利用该算法对抗干扰过程进行了仿真，仿真结果表明:与现有的抗干扰手段相比，该数据关联方法对解决红外干扰形成的假目标、目标遮挡等红外目标识别的难题，不仅实时性好，而且准确率高。

Infrared aircraft-flare discrimination using improved JPDA algorithm

It was a difficult problem in infrared target tracking field that how to effectively exclude the interference of infrared decoy, especially for that infrared decoy technique had developed more and more advanced as a common measure to interfer infrared tracking capability. Based on discussing characteristic difference of infrared targets and decoys, a multi-target tracking strategy to track excluding the infrared decoy was firstly proposed. And an improved joint probabilistic data association(JPDA) algorithm with fusion of multiple features was established. Finally, the process of tracking with excluding infrared decoy was simulated. Simulation results showed that the proposed algoritllIn can track target at real-time, which has higher accuracy for resolving the problem of the infrared target recognition that infrared decoys form false targets and the target block.