03514nam a22004815i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001800172072001600190072002300206072001500229100008500244245016100329250001800490264007200508300006900580336002600649337002600675338003600701347002400737505053400761520107501295650002302370650002302393650006602416650004202482700008402524700008302608700008202691710003402773773002602807776003602833776003602869776003602905856004602941912001402987912001403001999001703015978-981-99-9558-5DE-He21320251030111446.0cr nn 008mamaa240226s2024    si |    s    |||| 0|eng d  a97898199955859978-981-99-9558-57 a10.1007/978-981-99-9558-52doi 4aTK5101-5105.9 7aTJF2bicssc 7aTEC0240002bisacsh 7aTJF2thema1 aWang, Xiangrong.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut97183510aSparse Sensing and Sparsity Sensed in Multi-sensor Array Applicationsh[electronic resource] /cby Xiangrong Wang, Xianghua Wang, Weitong Zhai, Kaiquan Cai.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXVIII, 379 p. 168 illus., 165 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aFoundation -- Array Processing Fundamentals -- Multi-Sensor Array Applications -- Sparse Sensing via Antenna Selection -- Sparse Sensing for Determininic Beamforming -- Sparse Sensing for Adaptive Beamforming -- Cognitive-Driven Optimization of Sparse Sensing -- Sparse Sensing for MIMO Array Radar -- Sparse Sensing for Target Detection -- Sparse Sensing for Dual-Functional Radar Communications -- Sparsity Sensed using Sparse Arrays -- Sparsity Sensed with Thinned Antenna Array -- Sparsity Sensed for Enhanced DOA Estimation.  aThe book focuses on sparse multi-sensor array systems and design approaches. Both principles and engineering practice have been addressed, with more weight placed on algorithm development. This is achieved by providing an in-depth study on sparse sensing for several major multi-sensor array applications such as beam-pattern synthesis, adaptive beamforming, target detection, arrival angle estimation, and dual-functional radar communications. Sparsity sensed in multi-sensor arrays refers to the sparse property of the spatial spectrum sensed. The exploitation of the sparsity in the sensed can significantly enhance the performance of signal processing systems. The comprehensive and systematic treatment of theory and practice in different array applications is one of the major features of the book, which is particularly suited for readers who are interested to learn practical solutions in array signal processing. The book benefits researchers, engineers, and graduate students in the fields of signal processing, electrical engineering, telecommunications, etc. 0aTelecommunication. 0aSignal processing.14aMicrowaves, RF Engineering and Optical Communications.96575224aDigital and Analog Signal Processing.1 aWang, Xianghua.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9718361 aZhai, Weitong.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9718371 aCai, Kaiquan.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9718382 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981999557808iPrinted edition:z978981999559208iPrinted edition:z978981999560840uhttps://doi.org/10.1007/978-981-99-9558-5  aZDB-2-ENG  aZDB-2-SXE  c57909d57909