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Near-optimal estimation of radar pulse modulation waveform

机译：雷达脉冲调制波形的近最佳估计

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摘要

In this study, the authors focus on pulse modulation waveform estimation based on a sequence of intercepted pulses from the same radar emitter. In general, modulation waveform estimators first perform pulse alignment in time and frequency separately, and then accumulate the aligned pulses to estimate the waveform. However, commonly used alignment methods may lead to considerable alignment errors which are difficult to detect and compensate, especially under low signal-to-noise ratio (SNR) conditions, resulting in non-ideal effects of accumulation. This study proposes a robust and nearly optimal modulation waveform estimation algorithm. The new algorithm first aligns pulses in time and frequency jointly via the cross-ambiguity function to avoid the transfer and accumulation of alignment errors. After that, an iterative maximum-likelihood estimator is invoked to achieve the waveform estimation. Theoretical analysis and extensive experiments show that the proposed algorithm has much smaller alignment errors and better modulation waveform and modulation parameter estimation ability than competing methods at low SNRs, and can approach the ideal case. Moreover, this algorithm does not make any assumption on the type of modulation and is computationally efficient, thus having broad applications.
机译：在这项研究中，作者专注于基于来自同一雷达发射器的一系列截获脉冲的脉冲调制波形估计。通常，调制波形估计器首先在时间和频率上分别执行脉冲对准，然后累加对准的脉冲以估计波形。但是，常用的对准方法可能会导致相当大的对准误差，这些误差很难检测和补偿，尤其是在低信噪比（SNR）条件下，会导致非理想的累积效应。这项研究提出了一种鲁棒且接近最佳的调制波形估计算法。新算法首先通过交叉歧义函数共同在时间和频率上对齐脉冲，以避免对齐误差的传递和累积。之后，调用一个迭代的最大似然估计器以实现波形估计。理论分析和大量实验表明，与低信噪比的竞争方法相比，该算法具有更低的对准误差，更好的调制波形和调制参数估计能力，可以接近理想情况。而且，该算法不对调制类型做任何假设，并且计算效率高，因此具有广泛的应用。

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