Construction of an Arbitrary Waveform Radar System
Doctoral thesis, 2024

The thesis aims to develop and deploy continuous wave noise radar systems by addressing the self-interference issue and considering real-time implementation aspects. In contrast to the traditional pulse-Doppler radar, which generally operates with short, high-powered, and deterministic pulses, noise radars transmit continuous, low-powered, random, and preferably wideband signals. Noise radar systems offer several advantages over pulse-Doppler systems. The most notable (and desired) advantage is their low probability of interception properties — detecting and localizing a noise radar system is more challenging than a pulse-Doppler radar system.

However, few (or none) commercial or military noise radar systems exist due to the challenge of achieving relevant performance. The main problem is that self-interference, such as direct signal interference or clutter echoes, severely restricts the system's detection sensitivity. A significant amount of research has been dedicated to resolving the self-interference problem, and although good results have been achieved, more is required. Noise radar signal processing also requires high-speed digital electronics, and it is only recently that the performance of digital electronics has started to be on par with the requirements.

In this thesis, bistatic noise radar is considered a solution to the self-interference problem. By constructing a bistatic noise radar system, it is shown that separating the transmitter and receiver reduces the self-interference, thereby increasing the detection sensitivity. Furthermore, bistatic operation enables adaptive beamforming, which can be applied to further suppress self-interference — this is demonstrated using a multichannel receiver.

A real-time processor operating with a time-bandwidth product of 77 dB is implemented on a state-of-the-art field programmable gate array to investigate limiting aspects of real-time noise radar systems. The processor demonstrates that wideband noise radar systems are possible, but several limiting factors exist. One limitation is that operating with high time bandwidth products leads to several effects, such as range-walk, Doppler spread, and target decoherence, which must be managed. These effects are shown using offline data, and solutions are successfully applied. However, implementing these solutions in real-time systems is still an open question.

The most significant outcome of the thesis is the construction of a real-time bistatic noise radar system capable of detecting small UAVs at an operationally relevant distance of over 3.2 km. Minor improvements can significantly increase the detection range. This achievement demonstrates the readiness of noise radar technology for commercial adoption, reinforcing the thesis's primary goal.

Continous Wave Radar

Digital Beamforming

Clutter Filter

Low Probability of Intercept Radar

Air Surveillance Radar

Correlation Noise Floor

Noise Radar

Real-Time Radar

Range Walk

Bistatic Radar

Kollektron, MC2
Opponent: Prof. Daniel W. O´Hagan. Fraunhofer Institute FHR, Germany

Author

Martin Ankel

Chalmers, Microtechnology and Nanoscience (MC2), Quantum Technology

Implementation of a coherent real-time noise radar system

IET Radar, Sonar and Navigation,;Vol. 18(2024)p. 1002-1013

Journal article

Experimental Evaluation of Moving Target Compensation in High Time-Bandwidth Noise Radar

20th European Radar Conference, EuRAD 2023,;(2023)p. 213-216

Paper in proceeding

Bistatic noise radar: Demonstration of correlation noise suppression

IET Radar, Sonar and Navigation,;Vol. 17(2023)p. 351-361

Journal article

M. Ankel, R. Jonsson, M. Tholén, T. Bryllert, L. M. H. Ulander, and P. Delsing. Real-Time Bistatic Noise Radar with Adaptive Beamforming

M. Ankel, T. Bryllert and J. Backlund. Aspects of Operating Low-Cost Bistatic Radar Transmitters

The World’s Foremost Bistatic Noise Radar System

The rapid development and deployment of low-cost loitering munitions present an urgent and escalating threat to modern military radar systems. Given radars' critical role in maintaining situational awareness, their protection is paramount. Unfortunately, modern sensors are proficient at detecting the typical transmission pattern of short, high-powered pulses used by most radar systems. Noise radars, on the other hand, transmit continuous and random signals to confuse modern sensors, thereby evading detection and localization and increasing the likelihood of survival.

The challenge with continuous and random signals is that strong self-interference, which refers to the interference caused by the radar's transmitted signal, severely limits performance unless specialized signal processing is applied. Currently, the required specialized signal processing is too computationally demanding to implement real-time noise radar systems with relevant performance.

This thesis explores bistatic noise radar as a promising alternative to specialized signal processing in overcoming the self-interference problem. In bistatic radar systems, the transmitter and receiver are separated, significantly reducing self-interference and thus decreasing the signal processing's computational requirements, which enables the implementation of real-time noise radar systems.

The most significant result of this thesis is the successful implementation of a real-time bistatic noise radar system capable of detecting small unmanned aerial vehicles at an operationally relevant range of more than 3.2 km. Minor improvements will significantly increase the detection range, signifying that bistatic noise radars are a promising alternative for safeguarding future radar systems.

Areas of Advance

Information and Communication Technology

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

ISBN

978-91-8103-081-5

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5539

Publisher

Chalmers

Kollektron, MC2

Opponent: Prof. Daniel W. O´Hagan. Fraunhofer Institute FHR, Germany

More information

Latest update

8/27/2024