602 research outputs found
Radar Signal Processing for Interference Mitigation
It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter.
For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems.
The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically
Co-existence Between a Radar System and a Massive MIMO Wireless Cellular System
In this paper we consider the uplink of a massive MIMO communication system
using 5G New Radio-compliant multiple access, which is to co-exist with a radar
system using the same frequency band. We propose a system model taking into
account the reverberation (clutter) produced by the radar system at the massive
MIMO receiver. Then, we propose several linear receivers for uplink
data-detection, ranging by the simple channel-matched beamformer to the
zero-forcing and linear minimum mean square error receivers for clutter
disturbance rejection. Our results show that the clutter may have a strong
effect on the performance of the cellular communication system, but the use of
large-scale antenna arrays at the base station is key to provide increased
robustness against it, at least as far as data-detection is concerned.Comment: To be presented at 2018 IEEE SPAWC, Kalamata, Greece, June 201
Overlapped-MIMO Radar Waveform Design for Coexistence With Communication Systems
This paper explores an overlapped-multiple-input multiple-output (MIMO)
antenna architecture and a spectrum sharing algorithm via null space projection
(NSP) for radar-communications coexistence. In the overlapped-MIMO
architecture, the transmit array of a collocated MIMO radar is partitioned into
a number of subarrays that are allowed to overlap. Each of the antenna elements
in these subarrays have signals orthogonal to each other and to the elements of
the other subarrays. The proposed architecture not only improves sidelobe
suppression to reduce interference to communications system, but also enjoys
the advantages of MIMO radar without sacrificing the main desirable
characteristics. The radar-centric spectrum sharing algorithm then projects the
radar signal onto the null space of the communications system's interference
channel, which helps to avoid interference from the radar. Numerical results
are presented which show the performance of the proposed waveform design
algorithm in terms of overall beampattern and sidelobe levels of the radar
waveform and finally shows a comparison of the proposed system with existing
collocated MIMO radar architectures.Comment: accepted at IEEE WCN
Survey of Spectrum Sharing for Inter-Technology Coexistence
Increasing capacity demands in emerging wireless technologies are expected to
be met by network densification and spectrum bands open to multiple
technologies. These will, in turn, increase the level of interference and also
result in more complex inter-technology interactions, which will need to be
managed through spectrum sharing mechanisms. Consequently, novel spectrum
sharing mechanisms should be designed to allow spectrum access for multiple
technologies, while efficiently utilizing the spectrum resources overall.
Importantly, it is not trivial to design such efficient mechanisms, not only
due to technical aspects, but also due to regulatory and business model
constraints. In this survey we address spectrum sharing mechanisms for wireless
inter-technology coexistence by means of a technology circle that incorporates
in a unified, system-level view the technical and non-technical aspects. We
thus systematically explore the spectrum sharing design space consisting of
parameters at different layers. Using this framework, we present a literature
review on inter-technology coexistence with a focus on wireless technologies
with equal spectrum access rights, i.e. (i) primary/primary, (ii)
secondary/secondary, and (iii) technologies operating in a spectrum commons.
Moreover, we reflect on our literature review to identify possible spectrum
sharing design solutions and performance evaluation approaches useful for
future coexistence cases. Finally, we discuss spectrum sharing design
challenges and suggest future research directions
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