Abstract
In defense applications, the main features of radars are the Low Probability of Intercept (LPI) and the Low Probability of Exploitation (LPE). The counterpart uses more and more capable intercept receivers and signal processors thanks to the ongoing technological progress. Noise Radar Technology (NRT) is probably a very effective answer to the increasing demand for operational LPI/LPE radars. The design and selection of the radiated waveforms, while respecting the prescribed spectrum occupancy, has to comply with the contrasting requirements of LPI/LPE and of a favorable shape of the ambiguity function. Information theory seems to be a “technologically agnostic” tool to attempt to quantify the LPI/LPE capability of noise waveforms with little, or absent, a priori knowledge of the means and the strategies used by the counterpart. An information theoretical analysis can lead to practical results in the design and selection of NRT waveforms.
Highlights
The most relevant features of Noise Radar systems in defence applications are tightly related to modern Electronic Warfare (EW) systems, whose intercept, identification and jamming capabilities are quickly evolving following the evolution of radar threats
The remaining part of this paper is dedicated to the robustness of Noise Radar waveforms; for example, in Section 4.2 of [22] dedicated to Waveforms, it is claimed that a pure random-phase coded signal is the best waveform for CW Low Probability of Intercept (LPI)
A perfect Cryptographically Secure Pseudo-Random Number Generator (CSPRNG) would permit the implementation of an unbreakable cryptographic system, i.e., robust to any attack even using unlimited computation power. It is the celebrated one-time pad, in which each bit of the message is coded by addition (XOR operation) to the corresponding bit of the key, which is the output of the CSPRNG and decoded with the same operation by the legitimate recipient knowing the key
Summary
The most relevant features of Noise Radar systems in defence applications are tightly related to modern Electronic Warfare (EW) systems, whose intercept, identification and jamming capabilities are quickly evolving following the evolution of radar threats. In this case the jamming signal results from the aforementioned steps (a), (b) and (c) with the Machine Learning/Deep Learning analysis of the signals emitted by radar (see for instance [41]) according to their “signatures” and to their statistical features, and the comparison of the result with “a priori” information stored in the ad hoc “libraries” In this general frame, the remaining part of this paper is dedicated to the robustness of Noise Radar waveforms; for example, in Section 4.2 of [22] dedicated to Waveforms, it is claimed that a pure random-phase coded signal is the best waveform for CW LPI radar. This joint NR/EW sensor concept provides simultaneous operations of spectral sensing, jamming and radar target detection
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