基于最小细节熵准则的雷达网信号增强
Netted Radar Data Enhancement Based on Detail Entropy Minimization
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摘要: 提出了细节熵的概念,它能更真实地反映图像的清晰程度。采用最小细节熵准则对雷达网的数据进行融合。对于复杂目标采用迭代方法计算了最小细节熵准则所需的累加权值。为满足实际工作中实时性要求,采用神经网络来获取融合时的累加权值。
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关键词:
- 熵;神经网络;雷达网;融合;信噪比
Abstract: Detail entropy is proposed which can indicate the image clarity much accurately in the case of that image has slowly changed part. A technique based on detail entropy minimization principle is developed for fusing netted radar data. For complex radar target, the weights are calculated iteratively. But in consider of real-time requirement, the weights are gotten by neural network alternatively.
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