Detection of very low-SNR LFM signals with unknown start frequency and frequency rate is of great interest both in electronic support measure (ESM), and radio astronomy. The direct method for LFM signal detection needs a bank of matched-filters which is a really hardware consuming solution. As another solution, a bank of de-ramping blocks, followed by FFT units, can be used with the same performance as matched-filters bank. In such an alternative solution, with no optimization constraint, it is quite likely to reach a hardware extensive solution with limited processing gain. In this paper, a novel method based on de-ramping bank is proposed. Also, an optimization problem is developed, which could determine the optimum values for detection structure’s parameters, e.g. number of channels, as well as FFT length. It is shown that, the optimized detector features better processing gain in comparison to the non-optimized versions. Furthermore, adding a moving average at the output of the FFT could make remarkable improvement on detection performance. Moreover, the proposed detector is compared against the conventional methods in terms of detection performance and computational complexity characteristic, which aptly prove the superiority of the proposed method.

在电子支持措施（ESM）和射电天文学中，具有未知的起始频率和频率速率的非常低SNR LFM信号的检测都引起了极大的兴趣。用于LFM信号检测的直接方法需要一组匹配滤波器，这是真正消耗硬件的解决方案。作为另一种解决方案，可以使用一组解斜坡块，后跟FFT单元，其性能与匹配滤波器组相同。在这样的替代解决方案中，没有优化约束，很可能会获得具有有限处理增益的硬件扩展解决方案。本文提出了一种基于解斜坡库的新方法。同样，开发了一个优化问题，可以确定检测结构参数（例如通道数）和FFT长度的最佳值。结果表明，与未优化的版本相比，优化的检测器具有更好的处理增益。此外，在FFT的输出端添加移动平均值可以显着提高检测性能。此外，在检测性能和计算复杂度方面，将所提出的检测器与常规方法进行了比较，从而恰当地证明了所提出方法的优越性。