基于地磁传感技术的场面运动目标检测及跟踪预测研究

发布时间：2018-05-19 19:54

本文选题：跑道入侵 + 地磁传感技术　；参考：《南京航空航天大学》2016年硕士论文

【摘要】：场面运动目标检测与跟踪预测作为跑道入侵系统最为基础的系统监视功能部分,能够为目标识别和入侵控制提供信息支持,增强管制员的交通态势感知意识。针对现有场面监视设备的固有缺陷,本文展开基于地磁传感技术的场面运动目标检测与跟踪预测问题的研究。首先,本文采用单节点双AMR传感器方案对检测节点进行设计。结合场面运动目标背景及特点的先验信息,选择合理的布置方式构成检测节点网络以感知机场交通态势。其次,本文对自适应阈值检测算法进行改进,结合场面移动目标对地磁干扰信号的实际特征,设计了一种基于双AMR传感器的状态互补融合检测算法;根据不同的检测方式对目标的运行方向信息进行提取;本文提取了目标的平均速度和瞬时速度,提出了基于双地磁信号特征点的瞬时速度提取方法。再次,本文设计一种基于I-IMM的场面运动目标跟踪预测算法。在小样本速度观测信息的情况下,算法通过对残差均值加权求和重新构造模型概率似然函数,后验信息更新马尔科夫模型转移概率,加快了模型切换的速度并增加了模型辨识度。在目标状态不可感知阶段,利用可感知阶段辨识的运动模型及自适应的模型转移概率可实现对目标航迹的记忆跟踪预测。最后,本文设计开发了场面运动目标地磁信号采集系统。利用实地采集的目标地磁信号验证了本文提出的状态互补融合检测算法以及基于双地磁信号特征点提取目标瞬时速度方法的有效性。
[Abstract]:As the most basic monitoring function of runway intrusion system, scene motion target detection and tracking can provide information support for target recognition and intrusion control, and enhance traffic situation awareness of controllers. In view of the inherent defects of the existing scene monitoring equipment, this paper studies the detection and tracking of moving targets based on geomagnetic sensing technology. Firstly, the single node and double AMR sensor scheme is used to design the detection node. Based on the prior information of the background and characteristics of the scene motion target, the reasonable layout is chosen to form the detection node network to perceive the airport traffic situation. Secondly, this paper improves the adaptive threshold detection algorithm and designs a state complementary fusion detection algorithm based on dual AMR sensors. In this paper, the average velocity and instantaneous velocity of the target are extracted, and the instantaneous velocity extraction method based on the feature points of the double geomagnetic signal is proposed. Thirdly, this paper designs a scene motion target tracking and prediction algorithm based on I-IMM. In the case of small sample velocity observation, the algorithm reconstructs the probability likelihood function of the model by weighted sum of the residual mean, and updates the Markov model transfer probability by the posteriori information. The speed of model switching is accelerated and the model identification is increased. In the imperceptible phase of the target state, the motion model identified by the perceptible phase and the adaptive model transition probability can be used to predict the track of the target by memory tracking. Finally, a geomagnetic signal acquisition system is designed and developed. The effectiveness of the proposed state complementary fusion detection algorithm and the instantaneous velocity extraction method based on the feature points of the double geomagnetic signals are verified by using the geomagnetic signals collected in the field.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V355

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