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High Range Resolution Profile Estimation via a Cognitive Stepped Frequency Technique

机译：通过认知步进频率技术进行高分辨分辨率轮廓估计

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摘要

The problem of high range resolution profile (HRRP) estimation is considered in this paper. In particular, stepped frequency waveforms are devised to enhance the target range profile (RP) estimation accuracy. The basic idea relies on the dynamic optimization of the probing waveform accounting for some feedback information to minimize the profile estimation error. The transmitted frequency hopping pattern is selected so as to minimize the predicted Cramer-Rao lower bound (CRLB) associated with the amplitudes and locations of the scattering centers falling in the coarse range bin under test (i.e., the target profile). Specifically, it is assumed that the target imaging is initially performed via a conventional linear stepped frequency transmission, hence, based on the collected data, an initial prediction of the target profile is derived (perception). Then, the RP estimation is enhanced progressively according to the cognitive paradigm, via a specific frequency pattern selection at the next transmission (action). The results highlight the capabilities of the cognitive approach to provide interesting benefits with respect to the classic linear stepped frequency strategy.
机译：本文考虑了高分辨分辨率轮廓（HRRP）估计问题。特别是，设计了步进频率波形以增强目标范围轮廓（RP）的估计精度。基本思想依赖于探究波形的动态优化，其中考虑了一些反馈信息，以最大程度地减小轮廓估计误差。选择发射的跳频图案，以使与落入被测粗范围箱（即目标轮廓）中的散射中心的幅度和位置相关的预测的克莱默-拉奥下限（CRLB）最小。具体地，假设目标成像是通过常规的线性步进频率传输最初执行的，因此，基于收集的数据，得出目标轮廓的初始预测（感知）。然后，根据认知范例，在下一次传输（动作）时通过特定的频率模式选择来逐步增强RP估计。结果突出了认知方法相对于经典线性步进频率策略可提供有趣收益的功能。

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