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Neural fuzzy inference network approach to maneuvering target tracking

机译:神经模糊推理网络在机动目标跟踪中的应用

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摘要

In target tracking study, the fast target maneuver detecting and highly accurate tracking are very important. And it is difficult to be solved. For the radar/infrared image fused tracking system, a extend Kalman filter combines with a neural fuzzy inference network to be used in maneuvering target tracking. The features related to the target maneuver are extracted from radar, infrared measurements and outputs of tracking filter, and are sent into the neural fuzzy inference network as inputs firstly, and then the target's maneuver inputs are estimated, so that, the accurate tracking is achieved. The simulation results indicate that the new method is valuable for maneuvering target tracking.
机译:在目标跟踪研究中,快速的目标机动检测和高度精确的跟踪非常重要。而且很难解决。对于雷达/红外图像融合跟踪系统,扩展的卡尔曼滤波器与神经模糊推理网络相结合,可用于机动目标跟踪。从雷达,红外测量值和跟踪滤波器的输出中提取与目标机动有关的特征,并作为输入输入到神经模糊推理网络中,然后对目标的机动输入进行估计,从而实现对目标机动的准确跟踪。 。仿真结果表明,该新方法对于机动目标跟踪具有一定的参考价值。

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