1,629 research outputs found
OFDM Synthetic Aperture Radar Imaging with Sufficient Cyclic Prefix
The existing linear frequency modulated (LFM) (or step frequency) and random
noise synthetic aperture radar (SAR) systems may correspond to the frequency
hopping (FH) and direct sequence (DS) spread spectrum systems in the past
second and third generation wireless communications. Similar to the current and
future wireless communications generations, in this paper, we propose OFDM SAR
imaging, where a sufficient cyclic prefix (CP) is added to each OFDM pulse. The
sufficient CP insertion converts an inter-symbol interference (ISI) channel
from multipaths into multiple ISI-free subchannels as the key in a wireless
communications system, and analogously, it provides an inter-range-cell
interference (IRCI) free (high range resolution) SAR image in a SAR system. The
sufficient CP insertion along with our newly proposed SAR imaging algorithm
particularly for the OFDM signals also differentiates this paper from all the
existing studies in the literature on OFDM radar signal processing. Simulation
results are presented to illustrate the high range resolution performance of
our proposed CP based OFDM SAR imaging algorithm.Comment: This version has been accepted by IEEE Transactions on Geoscience and
Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing 201
Nearly orthogonal, doppler tolerant waveforms and signal processing for multi-mode radar applications
In this research, we investigate the design and analysis of nearly orthogonal, Doppler tolerant waveforms for diversity waveform radar applications. We then present a signal processing framework for joint synthetic aperture radar (SAR) and ground moving target indication (GMTI) processing that is built upon our proposed waveforms. ^ To design nearly orthogonal and Doppler tolerant waveforms, we applied direct sequence spread spectrum (DSSS) coding techniques to linear frequency modulated (LFM) signals. The resulting transmitted waveforms are rendered orthogonal using a unique spread spectrum code. At the receiver, the echo signal can be decoded using its spreading code. In this manner, transmit orthogonal waveforms can be matched filtered only with the intended receive signals. ^ Our proposed waveforms enable efficient SAR and GMTI processing concurrently without reconfiguring a radar system. Usually, SAR processing requires transmit waveforms with a low pulse repetition frequency (PRF) rate to reduce range ambigu- ity; on the other hand, GMTI processing requires a high PRF rate to avoid Doppler aliasing and ambiguity. These competing requirements can be tackled by employing some waveforms (with low PRF) for the SAR mission and other waveforms (with high PRF) for the GMTI mission. Since the proposed waveforms allow separation of individual waveforms at the receiver, we can accomplish both SAR and GMTI processing jointl
An investigation of a frequency diverse array
This thesis presents a novel concept for focusing an antenna beam pattern as a function
of range, time, and angle. In conventional phased arrays, beam steering is achieved by
applying a linear phase progression across the aperture. This thesis shows that by
applying an additional linear frequency shift across the elements, a new term is
generated which results in a scan angle that varies with range in the far-field.
Moreover, the antenna pattern is shown to scan in range and angle as a function of time.
These properties result in more flexible beam scan options for phased array antennas
than traditional phase shifter implementations. The thesis subsequently goes on to
investigate this phenomenon via full scale experimentation, and explores a number of
aspects of applying frequency diversity spatially across array antennas. This new form
of frequency diverse array may have applications to multipath mitigation, where a radio
signal takes two or more routes between the transmitter and receiver due to scattering
from natural and man-made objects. Since the interfering signals arrive from more than
one direction, the range-dependent and auto-scanning properties of the frequency
diverse array beam may be useful to isolate and suppress the interference. The
frequency diverse array may also have applications to wideband array steering, in lieu
of true time delay solutions which are often used to compensate for linear phase
progression with frequency across an array, and to sonar, where the speed of
propagation results in large percentage bandwidth, creating similar wideband array
effects. The frequency diverse array is also a stepping stone to more sophisticated joint
antenna and waveform design for the creation of new radar modes, such as simultaneous
multi-mode operation, for example, enabling joint synthetic aperture radar and ground
moving target indication
Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems
Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic
Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems.
Two Synthetic Aperture Radar (SAR) ATR algorithms are described for
full- and single-polarimetric images, and tested on the GOTCHA and the
MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments,
that, being discrete defined, provide better representations of targetsâ details. The proposed image moments based framework can be extended to
the availability of several images from multiple sensors through the implementation of a simple fusion rule.
A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopterâs rotor and received by
the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating
the number, the length and the rotation speed of the blades, parameters
that are peculiar for each helicopterâs model. The algorithm is extended to
deal with the identification of multiple helicopters flying in formation that
cannot be resolved in another domain. Moreover, a fusion rule is presented
to integrate the results of the identification performed from several sensors
in a distributed radar system. Tests performed both on simulated signals
and on real signals acquired from a scale model of a helicopter, confirm
the validity of the algorithm.
Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp
sub-carriers generated through the Fractional Fourier Transform (FrFT),
with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a
cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based
waveform is extensively tested and compared with Orthogonal Frequency
Division Multiplexing (OFDM) and LFM waveforms, in order to assess
both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic
Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems.
Two Synthetic Aperture Radar (SAR) ATR algorithms are described for
full- and single-polarimetric images, and tested on the GOTCHA and the
MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments,
that, being discrete defined, provide better representations of targetsâ details. The proposed image moments based framework can be extended to
the availability of several images from multiple sensors through the implementation of a simple fusion rule.
A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopterâs rotor and received by
the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating
the number, the length and the rotation speed of the blades, parameters
that are peculiar for each helicopterâs model. The algorithm is extended to
deal with the identification of multiple helicopters flying in formation that
cannot be resolved in another domain. Moreover, a fusion rule is presented
to integrate the results of the identification performed from several sensors
in a distributed radar system. Tests performed both on simulated signals
and on real signals acquired from a scale model of a helicopter, confirm
the validity of the algorithm.
Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp
sub-carriers generated through the Fractional Fourier Transform (FrFT),
with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a
cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based
waveform is extensively tested and compared with Orthogonal Frequency
Division Multiplexing (OFDM) and LFM waveforms, in order to assess
both its radar and communication performance
Waveform Design for MIMO Radar and SAR Application
Remote sensing applications using radar systems require specific signal processing to obtain high resolution for radar imagery. This high resolution is essential in detection and imaging processing and is provided by using synthetic aperture radar (SAR) processing. This chapter describes the application of the multiple-input multiple-output (MIMO) configuration and the orthogonal frequency-division multiplexing (OFDM) concept to overcome some existing limitations with conventional imaging systems as well as to assess the improvements achieved
Passive Synthetic Aperture Radar Imaging Using Commercial OFDM Communication Networks
Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection model is defined and signal processing approaches are proposed providing practical solutions to passive SAR imaging scenarios. Finally, experimental SAR images using general OFDM and WiMAX waveforms are shown to validate the overarching signal processing concept
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