1,635 research outputs found
MIMO Radar Target Localization and Performance Evaluation under SIRP Clutter
Multiple-input multiple-output (MIMO) radar has become a thriving subject of
research during the past decades. In the MIMO radar context, it is sometimes
more accurate to model the radar clutter as a non-Gaussian process, more
specifically, by using the spherically invariant random process (SIRP) model.
In this paper, we focus on the estimation and performance analysis of the
angular spacing between two targets for the MIMO radar under the SIRP clutter.
First, we propose an iterative maximum likelihood as well as an iterative
maximum a posteriori estimator, for the target's spacing parameter estimation
in the SIRP clutter context. Then we derive and compare various
Cram\'er-Rao-like bounds (CRLBs) for performance assessment. Finally, we
address the problem of target resolvability by using the concept of angular
resolution limit (ARL), and derive an analytical, closed-form expression of the
ARL based on Smith's criterion, between two closely spaced targets in a MIMO
radar context under SIRP clutter. For this aim we also obtain the non-matrix,
closed-form expressions for each of the CRLBs. Finally, we provide numerical
simulations to assess the performance of the proposed algorithms, the validity
of the derived ARL expression, and to reveal the ARL's insightful properties.Comment: 34 pages, 12 figure
Angular resolution limit for deterministic correlated sources
This paper is devoted to the analysis of the angular resolution limit (ARL),
an important performance measure in the directions-of-arrival estimation
theory. The main fruit of our endeavor takes the form of an explicit,
analytical expression of this resolution limit, w.r.t. the angular parameters
of interest between two closely spaced point sources in the far-field region.
As by-products, closed-form expressions of the Cram\'er-Rao bound have been
derived. Finally, with the aid of numerical tools, we confirm the validity of
our derivation and provide a detailed discussion on several enlightening
properties of the ARL revealed by our expression, with an emphasis on the
impact of the signal correlation
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Signal Processing in Large Systems: a New Paradigm
For a long time, detection and parameter estimation methods for signal
processing have relied on asymptotic statistics as the number of
observations of a population grows large comparatively to the population size
, i.e. . Modern technological and societal advances now
demand the study of sometimes extremely large populations and simultaneously
require fast signal processing due to accelerated system dynamics. This results
in not-so-large practical ratios , sometimes even smaller than one. A
disruptive change in classical signal processing methods has therefore been
initiated in the past ten years, mostly spurred by the field of large
dimensional random matrix theory. The early works in random matrix theory for
signal processing applications are however scarce and highly technical. This
tutorial provides an accessible methodological introduction to the modern tools
of random matrix theory and to the signal processing methods derived from them,
with an emphasis on simple illustrative examples
Contributions aux bornes inférieures de l’erreur quadratique moyenne en traitement du signal
A l’aide des bornes inférieures de l’erreur quadratique moyenne, la caractérisation du décrochement des estimateurs, l’analyse de la position optimale des capteurs dans un réseau ainsi que les limites de résolution statistiques sont étudiées dans le contexte du traitement d’antenne et du radar
Multiple-input Multiple-output Radar Waveform Design Methodologies
Multiple-input multiple-output (MIMO) radar is currently an active area of research. The MIMO techniques have been well studied for communications applications where they offer benefits in multipath fading environments. Partly inspired by these benefits, MIMO techniques are applied to radar and they offer a number of advantages such as improved resolution and sensitivity. It allows the use of transmitting multiple simultaneous waveforms from different phase centers. The employed radar waveform plays a key role in determining the accuracy, resolution, and ambiguity in performing tasks such as determining the target range, velocity, shape, and so on. The excellent performance promised by MIMO radar can be unleashed only by proper waveform design. In this article, a survey on MIMO radar waveform design is presented. The goal of this paper is to elucidate the key concepts of waveform design to encourage further research on this emerging technology.Defence Science Journal, 2013, 63(4), pp.393-401, DOI:http://dx.doi.org/10.14429/dsj.63.253
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