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Improving the Estimation of the Tracking Error Signal in Real Time for IR Seeker Using Nonlinear Kalman Filters

机译:使用非线性卡尔曼滤波器改善IR Seeker实时跟踪误差信号的估计

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摘要

In nonimaging IR seekers, the received target radiation on the IR detector is modulated via a reticle and produces the information signal (IS). The IS contains the tracking error signal (TES), which is proportional with the target position. TES is used in the control and optic section in the missile. The main task is to extract the TES from IS. The accuracy of TES extraction may be affected by several items such as noise from engines. In this paper, we used for the first time this field Square Root Unscented Kalman Filter (SRUKF) and Extended Kalman Filter (EKF) to estimate the TES from the IS for wagon wheel reticle.Due to the high computational complexity of these algorithms, their execution in real time is not an easy task especially if there is space limitation for hardware. By using the minicomputer, such as Raspberry Pi 3 Model B+ platform, the task can be done.The results showed that the SRUKF presented the best phase estimation for TES. The implementation by using Raspberry Pi was in real time because all algorithm executions for one period was less than 5ms, this time in our problem is less than strict timing window.
机译:在非映像IR寻求者中,通过掩模版调制IR检测器上的所接收的目标辐射,并产生信息信号(是)。该包含跟踪误差信号(TES),其与目标位置成比例。 TES用于导弹的控制和光学部分。主要任务是从IS中提取TES。 TES提取的准确性可能受到来自发动机噪声的几个物品的影响。在本文中,我们首次使用了这一字段广场root联络的卡尔曼滤波器(SRUKF)和扩展卡尔曼滤波器(EKF)来估计来自的TES是用于马车车轮φ的TES.DUE到这些算法的高计算复杂性,它们实时执行不是一件容易的任务,特别是如果硬件有空间限制。通过使用覆盆子PI 3型号B +平台的小型机,可以完成任务。结果表明SRUKF呈现了TES的最佳相位估计。使用raspberry pi的实现实时,因为一个时期的所有算法执行小于5ms,因此在我们的问题中的这一时间小于严格的时序窗口。

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