449 research outputs found
Wideband DOA Estimation via Sparse Bayesian Learning over a Khatri-Rao Dictionary
This paper deals with the wideband direction-of-arrival (DOA) estimation by exploiting the multiple measurement vectors (MMV) based sparse Bayesian learning (SBL) framework. First, the array covariance matrices at different frequency bins are focused to the reference frequency by the conventional focusing technique and then transformed into the vector form. Then a matrix called the Khatri-Rao dictionary is constructed by using the Khatri-Rao product and the multiple focused array covariance vectors are set as the new observations. DOA estimation is to find the sparsest representations of the new observations over the Khatri-Rao dictionary via SBL. The performance of the proposed method is compared with other well-known focusing based wideband algorithms and the Cramer-Rao lower bound (CRLB). The results show that it achieves higher resolution and accuracy and can reach the CRLB under relative demanding conditions. Moreover, the method imposes no restriction on the pattern of signal power spectral density and due to the increased number of rows of the dictionary, it can resolve more sources than sensors
Modelling Aspects of Planar Multi-Mode Antennas for Direction-of-Arrival Estimation
Multi-mode antennas are an alternative to classical antenna arrays, and hence
a promising emerging sensor technology for a vast variety of applications in
the areas of array signal processing and digital communications. An unsolved
problem is to describe the radiation pattern of multi-mode antennas in closed
analytic form based on calibration measurements or on electromagnetic field
(EMF) simulation data. As a solution, we investigate two modeling methods: One
is based on the array interpolation technique (AIT), the other one on wavefield
modeling (WM). Both methods are able to accurately interpolate quantized EMF
data of a given multi-mode antenna, in our case a planar four-port antenna
developed for the 6-8.5 GHz range. Since the modeling methods inherently depend
on parameter sets, we investigate the influence of the parameter choice on the
accuracy of both models. Furthermore, we evaluate the impact of modeling errors
for coherent maximum-likelihood direction-of-arrival (DoA) estimation given
different model parameters. Numerical results are presented for a single
polarization component. Simulations reveal that the estimation bias introduced
by model errors is subject to the chosen model parameters. Finally, we provide
optimized sets of AIT and WM parameters for the multi-mode antenna under
investigation. With these parameter sets, EMF data samples can be reproduced in
interpolated form with high angular resolution
Sensor array signal processing : two decades later
Caption title.Includes bibliographical references (p. 55-65).Supported by Army Research Office. DAAL03-92-G-115 Supported by the Air Force Office of Scientific Research. F49620-92-J-2002 Supported by the National Science Foundation. MIP-9015281 Supported by the ONR. N00014-91-J-1967 Supported by the AFOSR. F49620-93-1-0102Hamid Krim, Mats Viberg
Fundamental Imaging Limits of Radio Telescope Arrays
The fidelity of radio astronomical images is generally assessed by practical
experience, i.e. using rules of thumb, although some aspects and cases have
been treated rigorously. In this paper we present a mathematical framework
capable of describing the fundamental limits of radio astronomical imaging
problems. Although the data model assumes a single snapshot observation, i.e.
variations in time and frequency are not considered, this framework is
sufficiently general to allow extension to synthesis observations. Using tools
from statistical signal processing and linear algebra, we discuss the
tractability of the imaging and deconvolution problem, the redistribution of
noise in the map by the imaging and deconvolution process, the covariance of
the image values due to propagation of calibration errors and thermal noise and
the upper limit on the number of sources tractable by self calibration. The
combination of covariance of the image values and the number of tractable
sources determines the effective noise floor achievable in the imaging process.
The effective noise provides a better figure of merit than dynamic range since
it includes the spatial variations of the noise. Our results provide handles
for improving the imaging performance by design of the array.Comment: 12 pages, 8 figure
R-dimensional ESPRIT-type algorithms for strictly second-order non-circular sources and their performance analysis
High-resolution parameter estimation algorithms designed to exploit the prior
knowledge about incident signals from strictly second-order (SO) non-circular
(NC) sources allow for a lower estimation error and can resolve twice as many
sources. In this paper, we derive the R-D NC Standard ESPRIT and the R-D NC
Unitary ESPRIT algorithms that provide a significantly better performance
compared to their original versions for arbitrary source signals. They are
applicable to shift-invariant R-D antenna arrays and do not require a
centrosymmetric array structure. Moreover, we present a first-order asymptotic
performance analysis of the proposed algorithms, which is based on the error in
the signal subspace estimate arising from the noise perturbation. The derived
expressions for the resulting parameter estimation error are explicit in the
noise realizations and asymptotic in the effective signal-to-noise ratio (SNR),
i.e., the results become exact for either high SNRs or a large sample size. We
also provide mean squared error (MSE) expressions, where only the assumptions
of a zero mean and finite SO moments of the noise are required, but no
assumptions about its statistics are necessary. As a main result, we
analytically prove that the asymptotic performance of both R-D NC ESPRIT-type
algorithms is identical in the high effective SNR regime. Finally, a case study
shows that no improvement from strictly non-circular sources can be achieved in
the special case of a single source.Comment: accepted at IEEE Transactions on Signal Processing, 15 pages, 6
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Deterministic Cramer-Rao bound for strictly non-circular sources and analytical analysis of the achievable gains
Recently, several high-resolution parameter estimation algorithms have been
developed to exploit the structure of strictly second-order (SO) non-circular
(NC) signals. They achieve a higher estimation accuracy and can resolve up to
twice as many signal sources compared to the traditional methods for arbitrary
signals. In this paper, as a benchmark for these NC methods, we derive the
closed-form deterministic R-D NC Cramer-Rao bound (NC CRB) for the
multi-dimensional parameter estimation of strictly non-circular (rectilinear)
signal sources. Assuming a separable centro-symmetric R-D array, we show that
in some special cases, the deterministic R-D NC CRB reduces to the existing
deterministic R-D CRB for arbitrary signals. This suggests that no gain from
strictly non-circular sources (NC gain) can be achieved in these cases. For
more general scenarios, finding an analytical expression of the NC gain for an
arbitrary number of sources is very challenging. Thus, in this paper, we
simplify the derived NC CRB and the existing CRB for the special case of two
closely-spaced strictly non-circular sources captured by a uniform linear array
(ULA). Subsequently, we use these simplified CRB expressions to analytically
compute the maximum achievable asymptotic NC gain for the considered two source
case. The resulting expression only depends on the various physical parameters
and we find the conditions that provide the largest NC gain for two sources.
Our analysis is supported by extensive simulation results.Comment: submitted to IEEE Transactions on Signal Processing, 13 pages, 4
figure
Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank
A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques
Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank
A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques
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