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Sequential Monte Carlo Implementation for Infrared/Radar Maneuvering Target Tracking

机译:红外/雷达机动目标跟踪的顺序蒙特卡罗实现

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When the trace of the infrared small weak target is nonlinear and non-stationary which are always appear in fact, the state equation and measurement equation are nonlinear-nongauss and it is hard to get the solution using traditional algorithm. Take the high precision of both infrared angle measurement and radar resistant measurement into account, a new maneuvering target tracking algorithm fusing the measurement of infrared sensor and radar sensor is proposed. After the process of infrared/radar time registration and space registration, the measurement data after fusion is send into the resampling particle filter to track the target. The true state value is tracked by the posterior mean estimate of the state. Finally a simulation example is given and compared with the example of single radar target tracking, which is showed that the fusion tracking is better than single radar target tracking.
机译:当红外小弱目标的迹线是非线性的,并且始终出现的非静止性,状态方程和测量方程是非线性 - nongauss,并且很难使用传统算法来解决解决方案。提出了一种对红外角度测量和雷达抗性测量的高精度考虑,提出了一种融合红外传感器和雷达传感器的新的机动目标跟踪算法。在红外/雷达时间登记和空间登记过程之后,融合后的测量数据被发送到重采样粒子滤波器以跟踪目标。真正的状态值被状态的后部估计跟踪。最后给出了一个模拟示例,并与单个雷达目标跟踪的示例进行了比较,这表明融合跟踪优于单雷达目标跟踪。

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