72 research outputs found
Coherent FDA Receiver and Joint Range-Space-Time Processing
When a target is masked by mainlobe clutter with the same Doppler frequency,
it is difficult for conventional airborne radars to determine whether a target
is present in a given observation using regular space-time adaptive processing
techniques. Different from phased-array and multiple-input multiple-output
(MIMO) arrays, frequency diverse arrays (FDAs) employ frequency offsets across
the array elements, delivering additional range-controllable degrees of
freedom, potentially enabling suppression for this kind of clutter. However,
the reception of coherent FDA systems employing small frequency offsets and
achieving high transmit gain can be further improved. To this end, this work
proposes an coherent airborne FDA radar receiver that explores the
orthogonality of echo signals in the Doppler domain, allowing a joint
space-time processing module to be deployed to separate the aliased returns.
The resulting range-space-time adaptive processing allows for a preferable
detection performance for coherent airborne FDA radars as compared to current
alternative techniques.Comment: 11 pages, 9 figure
Optimum Design for Sparse FDA-MIMO Automotive Radar
Automotive radars usually employ multiple-input multiple-output (MIMO) antenna arrays to achieve high azimuthal resolution with fewer elements than a phased array. Despite this advantage, hardware costs and desired radar size limits the usage of more antennas in the array. Similar trade-off is encountered while attempting to achieve high range resolution which is limited by the signal bandwidth. However, nowadays given the demand for spectrum from communications services, wide bandwidth is not readily available. To address these issues, we propose a sparse variant of Frequency Diverse Array MIMO (FDA-MIMO) radar which enjoys the benefits of both FDA and MIMO techniques, including fewer elements, decoupling, and efficient joint estimation of target parameters. We then employ the Cram\'{e}r-Rao bound for angle and range estimation as a performance metric to design the optimal antenna placement and carrier frequency offsets for the transmit waveforms. Numerical experiments suggest that the performance of sparse FDA-MIMO radar is very close to the conventional FDA-MIMO despite 50\% reduction in the bandwidth and antenna elements
Suppression approach to main-beam deceptive jamming in FDA-MIMO radar using nonhomogeneous sample detection
Suppressing the main-beam deceptive jamming in traditional radar systems is challenging. Furthermore, the observations corrupted by false targets generated by smart deceptive jammers, which are not independent and identically distributed because of the pseudo-random time delay. This in turn complicates the task of jamming suppression. In this paper, a new main-beam deceptive jamming suppression approach is proposed, using nonhomogeneous sample detection in the frequency diverse array-multiple-input and multiple-output radar with non-perfectly orthogonal waveforms. First, according to the time delay or range difference, the true and false targets are discriminated in the joint transmit-receive spatial frequency domain. Subsequently, due to the range mismatch, the false targets are suppressed through a transmit-receive 2-D matched filter. In particular, in order to obtain the jamming-plus-noise covariance matrix with high accuracy, a nonhomogeneous sample detection method is developed. Simulation results are provided to demonstrate the detection performance of the proposed approach
Exploiting Sparse Structures in Source Localization and Tracking
This thesis deals with the modeling of structured signals under different sparsity constraints. Many phenomena exhibit an inherent structure that may be exploited when setting up models, examples include audio waves, radar, sonar, and image objects. These structures allow us to model, identify, and classify the processes, enabling parameter estimation for, e.g., identification, localisation, and tracking.In this work, such structures are exploited, with the goal to achieve efficient localisation and tracking of a structured source signal. Specifically, two scenarios are considered. In papers A and B, the aim is to find a sparse subset of a structured signal such that the signal parameters and source locations maybe estimated in an optimal way. For the sparse subset selection, a combinatorial optimization problem is approximately solved by means of convex relaxation, with the results of allowing for different types of a priori information to be incorporated in the optimization. In paper C, a sparse subset of data is provided, and a generative model is used to find the location of an unknown number of jammers in a wireless network, with the jammers’ movement in the network being tracked as additional observations become available
Waveform Diversity and Range-Coupled Adaptive Radar Signal Processing
Waveform diversity may offer several benefits to radar systems though often at the cost of reduced sensitivity. Multi-dimensional processing schemes are known to offer many degrees of freedom, which can be exploited to suppress the ambiguity inherent to pulse compression, array processing, and Doppler frequency estimation. Spatial waveform diversity can be achieved by transmitting different but correlated waveforms from each element of an antenna array. A simple yet effective scheme is employed to transmit different waveforms in different spatial directions. A new reiterative minimum mean squared error approach entitled Space-Range Adaptive Processing, which adapts simultaneously in range and angle, is derived and shown in simulation to offer enhanced performance when spatial waveform diversity is employed relative to both conventional matched filtering and sequentially adapting in angle and then range. The same mathematical framework is utilized to develop Time-Range Adaptive Processing (TRAP) algorithm which is capable of simultaneously adapting in Doppler frequency and range. TRAP is useful when pulse-to-pulse changing of the center frequency or waveform coding is used to achieve enhanced range resolution or unambiguous ranging, respectively. The inherent computational complexity of the new multi-dimensional algorithms is addressed by segmenting the full-dimension cost functions, yielding a reduced-dimensional variants of each. Finally, a non-adaptive approach based on the multi-dimensional TRAP signal model is utilized to develop an efficient clutter cancellation technique capable of suppressing multiple range intervals of clutter when waveform diversity is applied to pulse-Doppler radar
A comparison of processing approaches for distributed radar sensing
Radar networks received increasing attention in recent years as they can outperform
single monostatic or bistatic systems. Further attention is being dedicated
to these systems as an application of the MIMO concept, well know
in communications for increasing the capacity of the channel and improving
the overall quality of the connection. However, it is here shown that radar
network can take advantage not only from the angular diversity in observing
the target, but also from a variety of ways of processing the received signals. The
number of devices comprising the network has also been taken into the analysis.
Detection and false alarm are evaluated in noise only and clutter from a theoretical
and simulated point of view. Particular attention is dedicated to the statistics
behind the processing. Experiments have been performed to evaluate practical
applications of the proposed processing approaches and to validate assumptions
made in the theoretical analysis. In particular, the radar network used for
gathering real data is made up of two transmitters and three receivers. More than
two transmitters are well known to generate mutual interference and therefore
require additional e�fforts to mitigate the system self-interference. However,
this allowed studying aspects of multistatic clutter, such as correlation, which
represent a first and novel insight in this topic. Moreover, two approaches for
localizing targets have been developed. Whilst the first is a graphic approach, the
second is hybrid numerical (partially decentralized, partially centralized) which
is clearly shown to improve dramatically the single radar accuracy. Finally the
e�ects of exchanging angular with frequency diversity are shown as well in some
particular cases. This led to develop the Frequency MIMO and the Frequency
Diverse Array, according to the separation of two consecutive frequencies. The
latter is a brand new topic in technical literature, which is attracting the interest
of the technical community because of its potential to generate range-dependant
patterns. Both the latter systems can be used in radar-designing to improve the
agility and the effciency of the radar
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