双色红外成像制导自动目标识别与跟踪技术研究
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摘要
双色红外成像制导信息处理是双色红外成像导引头研制中的关键技术。本文结合“双色红外成像导引头图像处理机”的技术指标与实际应用,对基于红外双波段图像序列的目标检测、识别与跟踪技术进行了深入的研究。
全文共分五章。
第一章对双色红外成像制导信息处理技术进行了全面综述。本章针对双色红外成像导引头图像处理机的具体指标要求,在对国内外精确制导图像信息处理方案进行分析与比较的基础上,给出了双色红外成像制导信息处理的功能框图,确定了本文的主要研究内容及重点解决的问题。
第二章针对复杂背景下的弱目标检测问题,设计了一种基于红外双波段图像信息融合的弱目标检测方法。该方法基于算法融合和信息融合的基本思想,在目标检测的各个阶段充分利用了红外双波段图像信息的互补性和冗余性,较大程度地改善了系统对红外图像弱目标的检测性能。
第三章针对复杂条件下的点目标识别问题,提出了一种基于多特征多级分类的红外双波段图像点目标融合识别方法。该方法在提取目标的图像特征和时域特征等多种特征的基础上,采用基于D-S证据理论与类原型向量集的自适应K-近邻分类规则对红外双波段图像序列中的候选目标区域进行多级分类,显著地提高了系统的目标识别效率,为目标与诱饵辨别提供了合理的技术途经。
第四章针对双色红外成像系统中的机动目标跟踪问题,给出了一种采用模糊推理自适应加权融合的双色红外成像目标精确跟踪算法。该算法在对来自中波和长波红外成像传感器的实时图像分别进行目标偏移量滤波与估计的基础上,应用模糊推理技术来处理多传感器自适应加权融合过程中的不确定性,充分利用了多传感器在目标状态估计应用中的优势和数据冗余,提高了系统的跟踪精度,具有良好的工程实用性。
第五章对本文的研究内容及所取得的主要成果进行全面的总结,并指出了双色红外成像制导信息处理技术研究中需要进一步研究与探讨的问题。
The two color IR imaging guidance information processing is the key technology of the two color IR imaging seeker researching and manufacturing. The paper according to the practical application and the technological demand of the Two Color IR Imaging Seeker Image Processing System, researched the techniques of target detection、recognition and tracking based on the IR dual band image sequences comprehensively.
The paper totally has five chapters.
The technology of two color IR imaging guidance information processing is reviewed comprehensively in chapter one. Aim at the actual demand of the two color IR imaging seeker image processing system, proposed the functional frame of the two color imaging guidance information processing based on the analyzing and comparing of these schemes for the precision guidance image information processing in hometown and foreign literatures, and the primary researching contents of the paper and the key problems to resolve.
In chapter two, aim at the problem of weak target detection under the highly cluttered background, proposed a method of weak target based the IR dual band image information fusion. This method according to the basic idea of algorithm fusion and information fusion, take advantage of the complementary and redundant information contained in the IR dual band images at the different stage of target detection, improved the performance of the whole system's for IR image weak target detection to a great degree.
In chapter three, proposed a method of the IR dual band image dot target fusion recognition based on multi-features and hierarchical classification to resolve the problem of dot target recognition under the complex condition. The method firstly extracted the multiple features of target include the image features and temporal features, then classified these candidate target sub-image areas according to the feature vector representation using the adaptive K-Nearest Neighboring rule based the D-S evidential theory and the class prototype vector collection hierarchically. The method improved the system's target recognition efficiency to a great degree, presented a appropriate technique for the IR target and decoy discrimination.
In chapter four, aim at the problem of maneuvering target tracking in the two color IR imaging system, proposed an algorithm of the two IR imaging target precision tracking using fuzzy inference adaptive weighting fusion. This algorithm firstly estimated the offset of target in the two different band IR images by processing the real-time target images form the middle wave and long wave IR sensors respectively using the proposed method of IR imaging target based on algorithm fusion. Then adaptive weighted the local offset estimations of the two IR sensors using the fuzzy inference technique, and filtered and predicted the offset of target in IR image using the least square error adaptive lattice filter. The algorithm take advantage of the superiority and data redundancy of multiple sensors system in the application area of target states estimation, improved the target tracking precision and robustness of the whole system and showed the preferable application perspective.
Chapter five summarized the research content and primary contribution of this paper and probed into the application possibility of the two color IR imaging technology in these relative area.
全文共分五章。
第一章对双色红外成像制导信息处理技术进行了全面综述。本章针对双色红外成像导引头图像处理机的具体指标要求,在对国内外精确制导图像信息处理方案进行分析与比较的基础上,给出了双色红外成像制导信息处理的功能框图,确定了本文的主要研究内容及重点解决的问题。
第二章针对复杂背景下的弱目标检测问题,设计了一种基于红外双波段图像信息融合的弱目标检测方法。该方法基于算法融合和信息融合的基本思想,在目标检测的各个阶段充分利用了红外双波段图像信息的互补性和冗余性,较大程度地改善了系统对红外图像弱目标的检测性能。
第三章针对复杂条件下的点目标识别问题,提出了一种基于多特征多级分类的红外双波段图像点目标融合识别方法。该方法在提取目标的图像特征和时域特征等多种特征的基础上,采用基于D-S证据理论与类原型向量集的自适应K-近邻分类规则对红外双波段图像序列中的候选目标区域进行多级分类,显著地提高了系统的目标识别效率,为目标与诱饵辨别提供了合理的技术途经。
第四章针对双色红外成像系统中的机动目标跟踪问题,给出了一种采用模糊推理自适应加权融合的双色红外成像目标精确跟踪算法。该算法在对来自中波和长波红外成像传感器的实时图像分别进行目标偏移量滤波与估计的基础上,应用模糊推理技术来处理多传感器自适应加权融合过程中的不确定性,充分利用了多传感器在目标状态估计应用中的优势和数据冗余,提高了系统的跟踪精度,具有良好的工程实用性。
第五章对本文的研究内容及所取得的主要成果进行全面的总结,并指出了双色红外成像制导信息处理技术研究中需要进一步研究与探讨的问题。
The two color IR imaging guidance information processing is the key technology of the two color IR imaging seeker researching and manufacturing. The paper according to the practical application and the technological demand of the Two Color IR Imaging Seeker Image Processing System, researched the techniques of target detection、recognition and tracking based on the IR dual band image sequences comprehensively.
The paper totally has five chapters.
The technology of two color IR imaging guidance information processing is reviewed comprehensively in chapter one. Aim at the actual demand of the two color IR imaging seeker image processing system, proposed the functional frame of the two color imaging guidance information processing based on the analyzing and comparing of these schemes for the precision guidance image information processing in hometown and foreign literatures, and the primary researching contents of the paper and the key problems to resolve.
In chapter two, aim at the problem of weak target detection under the highly cluttered background, proposed a method of weak target based the IR dual band image information fusion. This method according to the basic idea of algorithm fusion and information fusion, take advantage of the complementary and redundant information contained in the IR dual band images at the different stage of target detection, improved the performance of the whole system's for IR image weak target detection to a great degree.
In chapter three, proposed a method of the IR dual band image dot target fusion recognition based on multi-features and hierarchical classification to resolve the problem of dot target recognition under the complex condition. The method firstly extracted the multiple features of target include the image features and temporal features, then classified these candidate target sub-image areas according to the feature vector representation using the adaptive K-Nearest Neighboring rule based the D-S evidential theory and the class prototype vector collection hierarchically. The method improved the system's target recognition efficiency to a great degree, presented a appropriate technique for the IR target and decoy discrimination.
In chapter four, aim at the problem of maneuvering target tracking in the two color IR imaging system, proposed an algorithm of the two IR imaging target precision tracking using fuzzy inference adaptive weighting fusion. This algorithm firstly estimated the offset of target in the two different band IR images by processing the real-time target images form the middle wave and long wave IR sensors respectively using the proposed method of IR imaging target based on algorithm fusion. Then adaptive weighted the local offset estimations of the two IR sensors using the fuzzy inference technique, and filtered and predicted the offset of target in IR image using the least square error adaptive lattice filter. The algorithm take advantage of the superiority and data redundancy of multiple sensors system in the application area of target states estimation, improved the target tracking precision and robustness of the whole system and showed the preferable application perspective.
Chapter five summarized the research content and primary contribution of this paper and probed into the application possibility of the two color IR imaging technology in these relative area.
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