The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal’s ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than −10 dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems.

中文翻译：

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仔细观察监控应用中的多普勒耐受噪声雷达波形

当代电子战 (EW) 中低拦截概率 (LPI) 和低概率利用 (LPE) 雷达的盛行对防御机制提出了持续的挑战，迫使保护策略不断进步。噪声雷达是 LPI 和 LPE 系统的例子，尽管存在多普勒容限有限的常见缺点，但它们在过去十年中获得了显着的关注。高级脉冲压缩噪声 (APCN) 波形是一种随机雷达信号，旨在将随机波形的 LPI 和 LPE 属性与线性频率调制固有的多普勒容差特征相结合。在目前的工作中，我们推导了描述 APCN 信号的模糊度函数和频谱包含的封闭式表达式，允许对其检测性能和消除范围模糊度作为其随机参数的函数进行正确分析。本文还对先前作品中声称的 APCN 信号的 LPI/LPE 特性进行了更详细的阐述。我们表明，采用时频分析 (TFA) 和图像处理方法的复杂电子情报 (ELINT) 系统可以拦截 APCN 并估计 APCN 波形的重要参数，例如带宽、工作频率、持续时间和脉冲重复间隔。我们还提出了一种旨在拦截和利用 APCN 波形独特特征的方法。其性能是根据此类 ELINT 系统检测到 APCN 雷达信号的概率作为 ELINT 系统中信噪比 (SNR) 的函数来评估的。我们评估了随机变量的准确性和精度，这些随机变量表征了所提出的估计器作为 SNR 的函数。结果表明，即使对于 SNR 略小于 -10 dB 的场景，检测概率也接近 1，并且表现出良好的性能。这项工作的贡献增强了噪声雷达功能，同时促进了 ESM 系统的改进。