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Resolution Enhancement with Model-Based Frequency Estimation Algorithms in Radar Signal Processing

机译：雷达信号处理中基于模型的频率估计算法提高分辨率

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摘要

In this work we present results on the improvement of resolution capability and accuracy for radar signal evaluation by means of model-based frequency estimation algorithms. In frequency modulated continuous wave radar sensors, which are widely used in industrial contactless distance measurement applications, the usage of the Fourier Transformation for signal evaluation is very common. Nevertheless, using the Fast Fourier Transformation, the resolution capability for closely spaced targets is limited and directly related to the employed signal bandwidth. Model-based frequency estimation algorithms, developed during the last decades, can essentially improve target resolution and distance accuracy. These improvements arc shown on simulation data as well as on measured data. Model order estimation, still a challenge when applying model-based evaluation techniques, is tackled by an adaptive approach.
机译：在这项工作中，我们介绍了通过基于模型的频率估计算法来提高雷达信号评估的分辨率和精度的结果。在广泛用于工业非接触式距离测量应用中的调频连续波雷达传感器中，使用傅里叶变换进行信号评估非常普遍。然而，使用快速傅立叶变换，对于紧密间隔的目标的分辨能力是有限的，并且与所采用的信号带宽直接相关。最近几十年来开发的基于模型的频率估计算法可以从根本上提高目标分辨率和距离精度。这些改进显示在模拟数据和测量数据上。通过应用自适应方法可以解决模型顺序估计问题，这在应用基于模型的评估技术时仍然是一个挑战。

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