Guest Editorial: Advancements and future trends in noise radar technology

The persuasive idea behind noise radar technology (NRT) states that the usage of random and non-periodic radar signals, in principle, eliminates all kinds of ambiguities that for many other radars are a driving design factor. However, practical aspects of NRT need to carefully evaluate the actual degree of randomness in their transmission, and the computational load the radar signal processing requires.

The performance of noise radars has evolved in accordance with the advance of signal processing hardware and algorithms. From the first implementations of noise radars which used analogue delay lines, for the observation of a limited range swath, towards modern and complex Field Programmable Gate Array-based real-time implementations, it took several decades of intense research. During the evolution of NRT, other advantageous characteristics of noise radars have been identified, particularly in the aspect of electronic warfare (EW). The latter, being seen as the counterpart of radar sensing, may have several goals such as the interception and location of radar emitters, the identification of the radar and or its platform, an estimation of the task of the radar, an assessment of the threat that is represented by the radar's task in a particular situation, and the engagement of counter-actions either by jamming, spoofing or a hard-kill. The modern and more general term EMSO (electromagnetic spectrum operations) draws an even wider picture around EW and includes cyber aspects as well. The latter, thus, introduces an interesting aspect for use-cases in which NRT is considered for joint communication and radar sensing applications.

The dear reader may be glad to see that this special issue on the advancements and future trends in noise radar contains contributions on anti-intercept features, security aspects, modern signal processing technology, such as programmable digital circuits and artificial intelligence.

The article ‘Implementation of a Coherent Real-Time Noise Radar System’ by Martin Ankel, Mats Tholén, Thomas Bryllert, Lars Ullander and Per Delsing focuses on the implementation aspects of a basic range-Doppler processing method. That algorithm is enhanced by a motion compensation approach that aims to overcome the cell migration in the range-Doppler plane caused by the high time-bandwith product of the selected parameters. This paper presents the implementation of a demonstrator system on a very detailed level. It not only reasons the authors' selection of particular Simulink® and Xilinx IP-cores but also discusses the requirements, limitations and effects that the selected RFSoC Hardware and its peripherals have on the implementation results. Finally, the paper reports the set up and results of field trials that illustrate the limitations of the demonstrator in accordance with what was expected from the theoretical assessment of the power budget, the waveform particularities and the hardware limitations. Interesting recommendations to overcome some major limitations complete this work.

Jaakko Marin, Micael Bernhardt and Taneli Riihonen contribute to this special issue by their work entitled ‘Full-duplex capable multifunction joint radar-communication-security transceiver with pseudonoise-Orthogonal Frequency-Division Multiplex (OFDM) mixture waveform’. The authors' work is driven by a use-case that includes two communicating parties and a third party, the eavesdropper, who tries to steal the information exchanged by the two first mentioned parties. A combined waveform of an OFDM communications signal and an in-band pseudo-random bandlimited noise sequence is selected to ensure successful information exchange, prevent the eavesdropper's attempt to de-code the OFDM sequence by the jamming effect the pseudo-noise signal has, and additionally, to successfully perform radar sensing. Influences such as self interference and mutual interference are considered as well. The simulation results presented in this work not only demonstrate the achievement of the tasks introduced by the use-case but also present performance assessments under some idealised conditions clearly stated in the discussion part of this work.

While eliminating range and Doppler ambiguities, the ability of NRT to withstand EW/Electronic Defence attacks is one of its main advantages. The article, ‘On the Anti-Intercept features of Noise Radars’ by Gaspare Galati and Gabriele Pavan presents a comparative analysis of the associated Low Probability of Detection (LPD), Low Probability of Interception (LPI) and of Exploitation (LPE) features for Continuous Emission Noise Radar (CE-NR) waveforms with varying ‘degrees of randomness’ and varied operational parameters, or ‘tailored’ waveforms. Time-frequency analysis is used to analyse three distinct noise radar waveforms, that is, a phase noise (advanced pulse compression noise) and two ‘tailored’ noise waveforms (FMeth and COSPAR). The article also discusses the detection of a radar signal by ESM or ELINT systems and includes simulation results regarding energy detector and multiple antennas receiver/correlator. Authors report that the LPD characteristics of a CE-NR are not substantially different from those of any CE radar transmitting deterministic waveforms when signal bandwith and duration is known a priori. Finally, the influence of tailoring, that is, sidelobe suppression is examined along with prospects for future work.

It is envisaged that radar sensors enhanced with Artificial Intelligence hold great potential for modern radar systems. The article ‘Artificial Intelligence Applications in Noise Radar Technology’ by Afonso Lobo Sénica, Paulo Alexandre Carapinha Marques and Mário Alexandre Teles de Figueiredo aims to present a broad overview of the research conducted on artificial intelligence (AI)-powered radar systems in last recent years and make recommendations on AI's potential applications in NRT. The study comprehensively surveys AI-based applications from the antenna design (beamforming, MIMO, leakage suppression), waveform optimization, signal interception, target interception/recognition/classification and interference suppression aspects with prospects for noise radar usage. Authors also provided the fundamental tools needed to comprehend how new AI-based techniques may be applied to radar technology, demonstrated how well it works for NRT, and most importantly provided benchmarks and guidance for further research on the subject.

This special issue covers many current topics, such as Artificial Intelligence, data security and integrity, the struggle with congested and contested spectral resources for different tasks, EW that seeks to dominate the electromagnetic spectrum, and an assessment of real-time implementation of noise radar sensing using state-of-the art signal processing hardware.

We hope that this special issue provides you with valuable insights into the advancements and future trends of noise radar technology and that you enjoy reading it.

Christoph Wasserzier: Conceptualization; writing—original draft; writing—review and editing. Kubilay Savci: Conceptualization; writing—original draft; writing—review and editing. Łukasz Masikowski: Conceptualization. Gaspare Galati: Conceptualization. Gabriele Pavan: Conceptualization.