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题名:
用于光电目标跟踪的数字滤波技术研究
作者: 杨子鹏
学位类别: 硕士
答辩日期: 2009-06-02
授予单位: 中国科学院光电技术研究所
授予地点: 光电技术研究所
导师: 蒋平
关键词: 光电目标跟踪 ; 卡尔曼滤波 ; 强跟踪自适应滤波器 ; 交互式多模型 ; 模型集自适应调整
学位专业: 计算机应用技术
中文摘要: 光电经纬仪是一种重要的光电跟踪测量设备,它的测量方式是被动跟踪测量。光电经纬仪对目标进行跟踪测量的过程中存在着目标脱靶量滞后、目标可能丢失以及各种噪声等问题,会影响到系统的跟踪精度及稳定性。为解决以上问题,需要在光电经纬仪跟踪系统中采用合适的预测滤波技术对得到的目标数据进行滤波,以补偿滞后量并减少随机噪声的影响,最终实现对目标的准确、稳定跟踪。 本文介绍了机动目标跟踪的原理和方法,分析了光电经纬仪的测量特点,建立了适用于光电目标跟踪的滤波模型。在对自适应滤波算法的研究中,将渐消因子和加速度方差自适应改进同时引入“当前”统计模型,提出了一种强跟踪自适应滤波器算法,该算法对于强机动、突发机动的目标有很好的跟踪性能,同时突破了加速度极限值对加速度方差计算的限制,无需机动检测,增大了机动目标的动态跟踪范围,在一定程度上提高了跟踪精度。接着对交互式多模型算法进行了一定研究,在理解交互式多模型算法的核心思想后,提出了一种机动目标跟踪的模型集自适应调整的多模型算法,该算法的思想是根据当前时刻多模型系统对目标加速度的总体估计和估计误差方差,调整模型间的间距和重新分配模型间的转移概率,使系统的模型集在下一时刻使用尽可能匹配目标运动模式,以提高系统的跟踪精度。 文中在提出新算法后,使用Matlab对算法进行了蒙特卡罗仿真,并与已有的标准算法进行了对比分析,以验证算法的正确性和有效性。
英文摘要: The photoelectric theodolite is one of the very important electro-optic equipments for target tracking and measuring, and it works in passive way. When using a photoelectric theodolite for target tracking, there are some problems, such as the time delay of target miss distance, temporary target lost, and signal noises and so on all these would have negative influences on the stability and tracking accuracy of the system. It is necessary to introduce appropriate prediction filtering technique to the photoelectric theodolite system to solve these problems. The technique could compensate the time delay; reduce the effect of random noise by filtering signals so that can help the system completing the steady and accurate target tracking. In this dissertation, the principles and mothods of target tracking are introduced, the characteristics of the photoelectric theodolite measurement are analyzed, and the suitable filtering model for electro-optic target tracking is established. In the research of adaptive filtering algorithm, a new algorithm is proposed, in which uses an improved adaptive Current Statistical model with a fading factor. This algorithm has higher performance for tracking the target's strong and sudden maneuver, due to introducing the fading factor of strong tracking filter and applying the improved variation of acceleration standard deviation synchronously. It can also eliminate the limitation of selection of the positive and negative acceleration maximum, and maneuver detecting is no longer needed. As consequence, this algorithm has a wide dynamic range and high accuracy for maneuvering target tracking. The interacting multiple model algorithm (IMM) is then studied. After comprehending the main idea of the IMM, a new adaptive IMM algorithm is presented. The new IMM algorithm has an adaptive model set, which would adjust the distance among models and update the model transfer probability according to the total acceleration estimation and its standard deviation. Benefit from the adaptive function, the model set would match well with the target's maneuver pattern, and the system would achieve better tracking performance resulting from that. The Monte Carlo simulations and comparison experiments with standard algorithms were done in Matlab to validate the correctness and efficiency of the new algorithms after they were proposed.
语种: 中文
内容类型: 学位论文
URI标识: http://ir.ioe.ac.cn/handle/181551/383
Appears in Collections:光电技术研究所博硕士论文_学位论文

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Recommended Citation:
杨子鹏. 用于光电目标跟踪的数字滤波技术研究[D]. 光电技术研究所. 中国科学院光电技术研究所. 2009.
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