8 research outputs found
Performance evaluation and waveform design for MIMO radar
Multiple-input multiple-output (MIMO) radar has been receiving increasing attention in recent
years due to the dramatic advantages offered by MIMO systems in communications. The
amount of energy reflected from a common radar target varies considerably with the observation
angle, and these scintillations may cause signal fading which severely degrades the performance
of conventional radars. MIMO radar with widely spaced antennas is able to view several
aspects of a target simultaneously, which realizes a spatial diversity gain to overcome the target
scintillation problem, leading to significantly enhanced system performance. Building on the
initial studies presented in the literature, MIMO radar is investigated in detail in this thesis.
First of all, a finite scatterers model is proposed, based on which the target detection performance
of a MIMO radar system with arbitrary array-target configurations is evaluated and
analyzed. A MIMO radar involving a realistic target is also set up, whose simulation results
corroborate the conclusions drawn based on theoretical target models, validating in a practical
setting the improvements in detection performance brought in by the MIMO radar configuration.
Next, a hybrid bistatic radar is introduced, which combines the phased-array and MIMO radar
configurations to take advantage of both coherent processing gain and spatial diversity gain
simultaneously. The target detection performance is first assessed, followed by the evaluation
of the direction finding performance, i.e., performance of estimating angle of arrival as well
as angel of departure. The presented theoretical expressions can be used to select the best
architecture for a radar system, particularly when the total number of antennas is fixed.
Finally, a novel two phase radar scheme involving signal retransmission is studied. It is based
on the time-reversal (TR) detection and is investigated to improve the detection performance
of a wideband MIMO radar or sonar system. Three detectors demanding various amounts
of a priori information are developed, whose performance is evaluated and compared. Three
schemes are proposed to design the retransmitted waveform with constraints on the transmitted
signal power, further enhancing the detection performance with respect to the TR approach
Passive MIMO Radar Detection
Passive multiple-input multiple-output (MIMO) radar is a sensor network comprised of multiple distributed receivers that detects and localizes targets using the emissions from multiple non-cooperative radio frequency transmitters. This dissertation advances the theory of centralized passive MIMO radar (PMR) detection by proposing two novel generalized likelihood ratio test (GLRT) detectors. The first addresses detection in PMR networks without direct-path signals. The second addresses detection in PMR networks with direct-path signals. The probability distributions of both test statistics are investigated using recent results from random matrix theory. Equivalence is established between PMR networks without direct-path signals and passive source localization (PSL) networks. Comparison of both detectors with a centralized GLRT for active MIMO radar (AMR) detection reveals that PMR may be interpreted as the link between AMR and PSL sensor networks. In particular, under high direct-path-to-noise ratio (DNR) conditions, PMR sensitivity and ambiguity approaches that of AMR. Under low-DNR conditions, PMR sensitivity and ambiguity approaches that of PSL. At intermediate DNRs, PMR sensitivity and ambiguity smoothly varies between that of AMR and PSL. In this way, PMR unifies PSL and AMR within a common theoretical framework. This result provides insight into the fundamental natures of active and passive distributed sensing
Compressive Sensing of Multiband Spectrum towards Real-World Wideband Applications.
PhD Theses.Spectrum scarcity is a major challenge in wireless communication systems with their
rapid evolutions towards more capacity and bandwidth. The fact that the real-world
spectrum, as a nite resource, is sparsely utilized in certain bands spurs the proposal
of spectrum sharing. In wideband scenarios, accurate real-time spectrum sensing, as an
enabler of spectrum sharing, can become ine cient as it naturally requires the sampling
rate of the analog-to-digital conversion to exceed the Nyquist rate, which is resourcecostly
and energy-consuming. Compressive sensing techniques have been applied in
wideband spectrum sensing to achieve sub-Nyquist-rate sampling of frequency sparse
signals to alleviate such burdens.
A major challenge of compressive spectrum sensing (CSS) is the complexity of the sparse
recovery algorithm. Greedy algorithms achieve sparse recovery with low complexity but
the required prior knowledge of the signal sparsity. A practical spectrum sparsity estimation
scheme is proposed. Furthermore, the dimension of the sparse recovery problem
is proposed to be reduced, which further reduces the complexity and achieves signal
denoising that promotes recovery delity. The robust detection of incumbent radio is
also a fundamental problem of CSS. To address the energy detection problem in CSS,
the spectrum statistics of the recovered signals are investigated and a practical threshold
adaption scheme for energy detection is proposed. Moreover, it is of particular interest to
seek the challenges and opportunities to implement real-world CSS for systems with large
bandwidth. Initial research on the practical issues towards the real-world realization of
wideband CSS system based on the multicoset sampler architecture is presented.
In all, this thesis provides insights into two critical challenges - low-complexity sparse
recovery and robust energy detection - in the general CSS context, while also looks
into some particular issues towards the real-world CSS implementation based on the
i
multicoset sampler
Safety and Reliability - Safe Societies in a Changing World
The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management
- mathematical methods in reliability and safety
- risk assessment
- risk management
- system reliability
- uncertainty analysis
- digitalization and big data
- prognostics and system health management
- occupational safety
- accident and incident modeling
- maintenance modeling and applications
- simulation for safety and reliability analysis
- dynamic risk and barrier management
- organizational factors and safety culture
- human factors and human reliability
- resilience engineering
- structural reliability
- natural hazards
- security
- economic analysis in risk managemen