603 research outputs found
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
In this paper, we present a robust multipath-based localization and mapping
framework that exploits the phases of specular multipath components (MPCs)
using a massive multiple-input multiple-output (MIMO) array at the base
station. Utilizing the phase information related to the propagation distances
of the MPCs enables the possibility of localization with extraordinary accuracy
even with limited bandwidth. The specular MPC parameters along with the
parameters of the noise and the dense multipath component (DMC) are tracked
using an extended Kalman filter (EKF), which enables to preserve the
distance-related phase changes of the MPC complex amplitudes. The DMC comprises
all non-resolvable MPCs, which occur due to finite measurement aperture. The
estimation of the DMC parameters enhances the estimation quality of the
specular MPCs and therefore also the quality of localization and mapping. The
estimated MPC propagation distances are subsequently used as input to a
distance-based localization and mapping algorithm. This algorithm does not need
prior knowledge about the surrounding environment and base station position.
The performance is demonstrated with real radio-channel measurements using an
antenna array with 128 ports at the base station side and a standard cellular
signal bandwidth of 40 MHz. The results show that high accuracy localization is
possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to
the IEEE Transaction on Wireless Communications for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
Matched-filtering and parameter estimation of ringdown waveforms
Using recent results from numerical relativity simulations of non-spinning
binary black hole mergers we revisit the problem of detecting ringdown
waveforms and of estimating the source parameters, considering both LISA and
Earth-based interferometers. We find that Advanced LIGO and EGO could detect
intermediate-mass black holes of mass up to about 1000 solar masses out to a
luminosity distance of a few Gpc. For typical multipolar energy distributions,
we show that the single-mode ringdown templates presently used for ringdown
searches in the LIGO data stream can produce a significant event loss (> 10%
for all detectors in a large interval of black hole masses) and very large
parameter estimation errors on the black hole's mass and spin. We estimate that
more than 10^6 templates would be needed for a single-stage multi-mode search.
Therefore, we recommend a "two stage" search to save on computational costs:
single-mode templates can be used for detection, but multi-mode templates or
Prony methods should be used to estimate parameters once a detection has been
made. We update estimates of the critical signal-to-noise ratio required to
test the hypothesis that two or more modes are present in the signal and to
resolve their frequencies, showing that second-generation Earth-based detectors
and LISA have the potential to perform no-hair tests.Comment: 19 pages, 9 figures, matches version in press in PR
Resolvability of objects from the standpoint of statistical parameter estimation
Radiance estimation and object resolvability by statistical parameter analysis of aperture fiel
On gravitational-wave spectroscopy of massive black holes with the space interferometer LISA
Newly formed black holes are expected to emit characteristic radiation in the
form of quasi-normal modes, called ringdown waves, with discrete frequencies.
LISA should be able to detect the ringdown waves emitted by oscillating
supermassive black holes throughout the observable Universe. We develop a
multi-mode formalism, applicable to any interferometric detectors, for
detecting ringdown signals, for estimating black hole parameters from those
signals, and for testing the no-hair theorem of general relativity. Focusing on
LISA, we use current models of its sensitivity to compute the expected
signal-to-noise ratio for ringdown events, the relative parameter estimation
accuracy, and the resolvability of different modes. We also discuss the extent
to which uncertainties on physical parameters, such as the black hole spin and
the energy emitted in each mode, will affect our ability to do black hole
spectroscopy.Comment: 44 pages, 21 figures, 10 tables. Minor changes to match version in
press in Phys. Rev.
Statistical Resolution Limit for the Multidimensional Harmonic Retrieval Model: Hypothesis Test and Cramer-Rao Bound Approaches
Special issue on Advances in Angle-of-Arrival and Multidimensional Signal Processing for Localization and CommunicationsInternational audienceThe Statistical Resolution Limit (SRL), which is defined as the minimal separation between parameters to allow a correct resolvability, is an important statistical tool to quantify the ultimate performance for parametric estimation problems. In this paper we generalize the concept of the SRL to the Multidimensional SRL (MSRL) applied to the multidimensional harmonic retrieval model. In this paper, we derive the SRL for the so-called multidimensional harmonic retrieval model by using a generalization of the previously introduced SRL concepts that we call Multidimensional SRL (MSRL). We first derive the MSRL using an hypothesis test approach. This statistical test is shown to be asymptotically an uniformly most powerful test which is the strongest optimality statement that one could expect to obtain. Second, we link the proposed asymptotic MSRL based on the hypothesis test approach to a new extension of the SRL based on the Cramér-Rao Bound approach. Thus, a closed-form expression of the asymptotic MSRL is given and analyzed in the framework of the multidimensional harmonic retrieval model. Particularly, it is proved that the optimal MSRL is obtained for equi-powered sources and/or an equi-distributed number of sensors on each multi-way array
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