Sensor arrays have been widely applied in various fields, e.g., wireless communication, radar, and navigation. Key roles of sensor arrays include providing spatial parameter estimations and enhancing parameter estimation performances in other domains. However, with the present complex electromagnetic environment, general estimation methods experience significant performance degradations when encountering complex signal propagation, such as multipath or occlusion situations. Meanwhile, a sensor array system itself also suffers from uncertainties, such as gain-phase errors and mutual coupling, which are classic but long-term problems. In this Special Issue, we have collected a range of representative research works on this topic. In response to errors in the sensor array itself, such as random array deformations and mutual coupling, sparse array design and small-aperture antenna design methods are proposed. Meanwhile, from a parameter estimation perspective, conformal maps, element selection, and deep learning-based methods are proposed. In response to the received data errors caused by complex environments, such as multipath propagation and low signal-to-noise ratios, methods based on reweighted sparse sensing, pseudo noise resampling, Bayesian estimation, and multiphase filters are proposed. Furthermore, in response to the high complexity brought by robust processing algorithms, methods such as Taylor Compensation and dimensionality reduction are proposed. The relevant methods have shown excellent performance under complex system errors through simulation tests or actual tests.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 50508964-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Sensor arrays have been widely applied in various fields, e.g., wireless communication, radar, and navigation. Key roles of sensor arrays include providing spatial parameter estimations and enhancing parameter estimation performances in other domains. However, with the present complex electromagnetic environment, general estimation methods experience significant performance degradations when encountering complex signal propagation, such as multipath or occlusion situations. Meanwhile, a sensor array system itself also suffers from uncertainties, such as gain-phase errors and mutual coupling, which are classic but long-term problems. In this Special Issue, we have collected a range of representative research works on this topic. In response to errors in the sensor array itself, such as random array deformations and mutual coupling, sparse array design and small-aperture antenna design methods are proposed. Meanwhile, from a parameter estimation perspective, conformal maps, element selection, and deep learning-based methods are proposed. In response to the received data errors caused by complex environments, such as multipath propagation and low signal-to-noise ratios, methods based on reweighted sparse sensing, pseudo noise resampling, Bayesian estimation, and multiphase filters are proposed. Furthermore, in response to the high complexity brought by robust processing algorithms, methods such as Taylor Compensation and dimensionality reduction are proposed. The relevant methods have shown excellent performance under complex system errors through simulation tests or actual tests. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783725843930
Quantité disponible : 1 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783725843930
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50508964
Quantité disponible : Plus de 20 disponibles
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
Hardback or Cased Book. Etat : New. Robust Parameter Estimation with Sensor Arrays in Complex Electromagnetic Environments. Book. N° de réf. du vendeur BBS-9783725843930
Quantité disponible : 5 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 50508964-n
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 50508964
Quantité disponible : Plus de 20 disponibles
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. Sensor arrays have been widely applied in various fields, e.g., wireless communication, radar, and navigation. Key roles of sensor arrays include providing spatial parameter estimations and enhancing parameter estimation performances in other domains. However, with the present complex electromagnetic environment, general estimation methods experience significant performance degradations when encountering complex signal propagation, such as multipath or occlusion situations. Meanwhile, a sensor array system itself also suffers from uncertainties, such as gain-phase errors and mutual coupling, which are classic but long-term problems. In this Special Issue, we have collected a range of representative research works on this topic. In response to errors in the sensor array itself, such as random array deformations and mutual coupling, sparse array design and small-aperture antenna design methods are proposed. Meanwhile, from a parameter estimation perspective, conformal maps, element selection, and deep learning-based methods are proposed. In response to the received data errors caused by complex environments, such as multipath propagation and low signal-to-noise ratios, methods based on reweighted sparse sensing, pseudo noise resampling, Bayesian estimation, and multiphase filters are proposed. Furthermore, in response to the high complexity brought by robust processing algorithms, methods such as Taylor Compensation and dimensionality reduction are proposed. The relevant methods have shown excellent performance under complex system errors through simulation tests or actual tests. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783725843930
Quantité disponible : 1 disponible(s)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26404581793
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand. N° de réf. du vendeur 409653886
Quantité disponible : 4 disponible(s)