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针对传感器观测的数据可能存在不完整、缺失的情况,提出了基于支持向量机分类器的空中目标智能融合识别模型。首先,介绍了目标融合识别的原理和层次模型。其次,探讨工程上的需求及其应用,并给出仿真实例。从优化算法的角度上,讨论了将Boost-SVM理论应用于目标融合识别。该模型进行仿真,能较精确的识别目标。最后,进行两种模型识别结果的对比并提出了改进措施。
According to the incomplete or missing data of sensor observation, an air target intelligent fusion recognition model based on SVM classifier is proposed. First of all, the principle and hierarchical model of target fusion recognition are introduced. Secondly, discuss the engineering requirements and its application, and give the simulation examples. From the perspective of optimization algorithm, the application of Boost-SVM theory to target fusion recognition is discussed. The model is emulated to identify targets more accurately. Finally, the comparison of the results of the two models and the improvement measures are proposed.