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UNMANNED AERIAL VEHICLE INFRARED DETECTOR SIMULATION MODELLING AND PERFORMANCE ANALYSIS

机译:空中车载红外探测器的仿真建模与性能分析

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An observation model of unmanned aerial vehicle(UAV) infrared detector is developed. The visibility criterion is derived via geometric relationships between the infrared detector, target and earth, the constraint of the detector's frame angle, and the detection range of infrared detector. Because of the infrared sensor can only obtain the angular information of the target, so it is impossible for one detector to locate position of the target. The position of the target is obtained by two or more detectors. The least square method based multi-sensor target tracking method is introduced. It is important to set a filter before using the tracking data as there are observation errors caused by UAV position error, UAV attitude error, sensor pointing error and sensor image plane position error. The extend Kalman Filter (EKF) algorithm is used to smooth the tracking signals. Finally, two UAV infrared detectors observing a low-orbit target is simulated for their observation performance. The result shows that the infrared detectors can observe the target within the scope of the detection range. When the target flies off the top of the UAV, the detectors can't observe it because of the constraint of the frame angle. The observation error is reduced substantially after the EKF is used.
机译:建立了无人机红外探测器的观测模型。可见性标准是通过红外探测器,目标与地球之间的几何关系,探测器镜框角度的约束以及红外探测器的探测范围得出的。由于红外传感器只能获取目标的角度信息,因此一个探测器不可能定位目标的位置。目标的位置由两个或多个检测器获得。介绍了基于最小二乘法的多传感器目标跟踪方法。使用跟踪数据之前,请务必设置过滤器,因为存在由无人机位置误差,无人机姿态误差,传感器指向误差和传感器图像平面位置误差引起的观察误差。扩展卡尔曼滤波器(EKF)算法用于平滑跟踪信号。最后,模拟了两个观察低轨道目标的无人机红外探测器的观测性能。结果表明,红外探测器可以在探测范围内观察目标。当目标飞离无人机顶部时,由于镜架角度的限制,探测器无法观察到它。使用EKF后,观察误差会大大降低。

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