光电成像跟踪系统需要保证不同目标的自适应识别, 同时严格按照时间序列执行的图像处理又是一个强实时性过程。实时融合跟踪技术提出并行执行多个算法组以适应不同类型目标的识别, 并通过像素级、特征级和决策级的同时融合处理保证了系统跟踪的稳定性, 最后在嵌入式并行处理硬件平台上有效解决了对运动目标的自适应跟踪。文中详细阐述了实时融合跟踪技术的技术思想和技术路线, 在剖析其并行结构的基础上完成了光电成像跟踪系统的嵌入式硬件并行平台的设计和实现, 取得了显著的工程应用成果。

Opto-electronic imaging and tracking system must be guaranteed to recognize a variety of targets. Meanwhile, the scheduled image processing is a hard real-time processing course. Our studies have developed a real-time tracking fusion approach including pixel-base, feature-based and decision-based fusion, which simultaneously run multiple algorithms suiting to independently analyze and obtain various feature of targets for satisfying different targets in different tasks. A prototype has been developed to adaptively track motive objects. The paper introduces in detail the idea and method of real-time tracking fusion technology, and specifies hardware design and algorithm performance by analyzing embedded parallel architecture. The reliability, stability, adaptivity and real-time performance of the approach have been widely proven in real applications.