301 research outputs found
Generalized DFT: extensions in communications
Discrete Fourier Transform (DFT) is a restricted version of Generalized DFT (GDFT) which offers a very limited number of sets to be used in a multicarrier communication system. In contrast, as an extension on Discrete Fourier Transform (DFT) from the linear phase to non-linear phase, the proposed GDFT provides many possible carrier sets of various lengths with comparable or better performance than DFT. The availability of the rich library of orthogonal constant amplitude transforms with good performance allows people to design adaptive systems where user code allocations are made dynamically to exploit the current channel conditions in order to deliver better performance.
For MIMO Radar systems, the ideal case to detect a moving target is when all waveforms are orthogonal, which can provide an accurate estimation. But this is not practical in distributed MIMO radars, where sensors are at varying distances from a target. Orthogonal waveforms with low auto- and cross-correlations are of great interest for MIMO radar applications with distributed antennas. Finite length orthogonal codes are required in real-world applications where frequency selectivity and signal correlation features of the optimal subspace are compromised. In the first part of the dissertation, a method is addressed to design optimal waveforms which meets above requirements for various radar systems by designing the phase shaping function (PSF) of GDFT framework with non-linear phase.
Multicarrier transmission such as orthogonal frequency-division multiplexing (OFDM) has seen a rise in popularity in wireless communication, as it offers a promising choice for high speed data rate transmission. Meanwhile, high peak-to-average power ratio (PAPR) is one of the well-known drawbacks of the OFDM system due to reduced power efficiency in non-linear modules. Such a situation leads to inefficient amplification and increases the cost of the system, or increases in interference and signal distortion. Therefore, PAPR reduction techniques play an essential role to improve power efficiency in the OFDM systems. There has been a variety of PAPR reduction methods emphasizing different aspects proposed in the literature. The trade-off for PAPR reduction in the existing methods is either increased average power and/or added computational complexity. A new PAPR reduction scheme is proposed that implements a pre-designed symbol alphabet modifier matrix (SAM) to jointly modify the amplitude and phase values of the original data symbol alphabets prior to the IFFT operation of an OFDM system at the transmitter. The method formulated with the GDFT offers a low-complexity framework in four proposed cases devised to be independent of original data symbols. Without degrading the bit error rate (BER) performance, it formulates PAPR reduction problem elegantly and outperforms partial transmit sequences (PTS), selected mapping technique (SLM) and Walsh Hadamard transform (WHT-OFDM) significantly for the communication scenarios considered in the dissertation
MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter
The concept of multiple-input multiple-output (MIMO) radar allows each transmitting antenna element to transmit an arbitrary waveform. This provides extra degrees of freedom compared to the traditional transmit beamforming approach. It has been shown in the recent literature that MIMO radar systems have many advantages. In this paper, we consider the joint optimization of waveforms and receiving filters in the MIMO radar for the case of extended target in clutter. A novel iterative algorithm is proposed to optimize the waveforms and receiving filters such that the detection performance can be maximized. The corresponding iterative algorithms are also developed for the case where only the statistics or the uncertainty set of the target impulse response is available. These algorithms guarantee that the SINR performance improves in each iteration step. Numerical results show that the proposed methods have better SINR performance than existing design methods
Estudo de formas de onda e conceção de algoritmos para operação conjunta de sistemas de comunicação e radar
The focus of this thesis is the processing of signals and design of algorithms
that can be used to enable radar functions in communications systems.
Orthogonal frequency division multiplexing (OFDM) is a popular multicarrier
modulation waveform in communication systems. As a wideband
signal, OFDM improves resolution and enables spectral efficiency in radar
systems, while also improving detection performance thanks to its inherent
frequency diversity. This thesis aims to use multicarrier waveforms for radar
systems, to enable the simultaneous operation of radar and communication
functions on the same device. The thesis is divided in two parts. The first
part, studies the adaptation and application of other multicarrier waveforms
to radar functions. At the present time many studies have been carried out
to jointly use the OFDM signal for communication and radar functions, but
other waveforms have shown to be possible candidates for communication
applications. Therefore, studies on the evaluation of the application of these
same signals to radar functions are necessary. In this thesis, to demonstrate
that other multicarrier waveforms can overcome the OFDM waveform
in radar/communication (RadCom) systems, we propose the adaptation of
the filter bank multicarrier (FBMC), generalized frequency division multiplexing
(GFDM) and universal filtering multicarrier (UFMC) waveforms for radar
functions. These alternative waveforms were compared performance-wise
regarding achievable target parameter estimation performance, amount of
residual background noise in the radar image, impact of intersystem interference
and flexibility of parameterization. In the second part of the thesis,
signal processing techniques are explored to solve some of the limitations
of the use of multicarrier waveforms for RadCom systems. Radar systems
based on OFDM are promising candidates for future intelligent transport networks.
Exploring the dual functionality enabled by OFDM, we presents cooperative
methods for high-resolution delay-Doppler and direction-of-arrival
estimation. High-resolution parameter estimation is an important requirement
for automotive radar systems, especially in multi-target scenarios that
require reliable target separation performance. By exploring the cooperation
between vehicles, the studies presented in this thesis also enable the distributed
tracking of targets. The result is a highly accurate multi-target tracking
across the entire cooperative vehicle network, leading to improvements
in transport reliability and safety.O foco desta tese é o processamento de sinais e desenvolvimento de algoritmos
que podem ser utilizados para a habilitar a função de radar nos sistemas
de comunicação. OFDM (Orthogonal Frequency Division Multiplexing)
é uma forma de onda com modulação multi-portadora, popular em sistemas
de comunicação. Para sistemas de radar, O OFDM melhora a resolução e
fornece eficiência espectral, além disso sua diversidade de frequências melhora
o desempenho na detecção do radar. Essa tese tem como objetivo
utilizar formas de onda multi-portadoras para sistemas de radar, possibilitando
a operação simultânea de funções de radar e de comunicação num
mesmo dispositivo. A tese esta dividida em duas partes. Na primeira parte
da tese são realizados estudos da adaptabilidade de outras formas de onda
multi-portadora para funções de radar. Nos dias atuais, muitos estudos sobre
o uso do sinal OFDM para funções de comunicação e radar vêm sendo
realizados, no entanto, outras formas de onda mostram-se possíveis candidatas
a aplicações em sistemas de comunicação, e assim, avaliações para
funções de sistema de radar se tornam necessárias. Nesta tese, com a
intenção de demonstrar que formas de onda multi-portadoras alternativas
podem superar o OFDM nos sistemas de Radar/comunicação (RadCom),
propomos a adaptação das seguintes formas de onda: FBMC (Filter Bank
Multicarrier); GFDM (Generalized Frequency Division Multiplexing); e UFMC
(Universal Filtering Multicarrier) para funções de radar. Também produzimos
uma análise de desempenho dessas formas de onda sobre o aspecto
da estimativa de parâmetros-alvo, ruído de fundo, interferência entre sistemas
e parametrização do sistema. Na segunda parte da tese serão explorados
técnicas de processamento de sinal de forma a solucionar algumas
das limitações do uso de formas de ondas multi-portadora para sistemas
RadCom. Os sistemas de radar baseados no OFDM são candidatos
promissores para futuras redes de transporte inteligentes, porque combinam
funções de estimativa de alvo com funções de rede de comunicação
em um único sistema. Explorando a funcionalidade dupla habilitada pelo
OFDM, nesta tese, apresentamos métodos cooperativos de alta resolução
para estimar o posição, velocidade e direção dos alvos. A estimativa de
parâmetros de alta resolução é um requisito importante para sistemas de
radar automotivo, especialmente em cenários de múltiplos alvos que exigem
melhor desempenho de separação de alvos. Ao explorar a cooperação entre
veículos, os estudos apresentados nesta tese também permitem o rastreamento
distribuído de alvos. O resultado é um rastreamento multi-alvo altamente
preciso em toda a rede de veículos cooperativos, levando a melhorias
na confiabilidade e segurança do transporte.Programa Doutoral em Telecomunicaçõe
Frequency Diverse Array Radar: Signal Characterization and Measurement Accuracy
Radar systems provide an important remote sensing capability, and are crucial to the layered sensing vision; a concept of operation that aims to apply the right number of the right types of sensors, in the right places, at the right times for superior battle space situational awareness. The layered sensing vision poses a range of technical challenges, including radar, that are yet to be addressed. To address the radar-specific design challenges, the research community responded with waveform diversity; a relatively new field of study which aims reduce the cost of remote sensing while improving performance. Early work suggests that the frequency diverse array radar may be able to perform several remote sensing missions simultaneously without sacrificing performance. With few techniques available for modeling and characterizing the frequency diverse array, this research aims to specify, validate and characterize a waveform diverse signal model that can be used to model a variety of traditional and contemporary radar configurations, including frequency diverse array radars. To meet the aim of the research, a generalized radar array signal model is specified. A representative hardware system is built to generate the arbitrary radar signals, then the measured and simulated signals are compared to validate the model. Using the generalized model, expressions for the average transmit signal power, angular resolution, and the ambiguity function are also derived. The range, velocity and direction-of-arrival measurement accuracies for a set of signal configurations are evaluated to determine whether the configuration improves fundamental measurement accuracy
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