BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Taipei BEGIN:STANDARD DTSTART:19790930T230000 TZOFFSETFROM:+0900 TZOFFSETTO:+0800 TZNAME:CST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250515T062731Z UID:27DA067E-61A0-4D2C-80F0-77B3DFFB6A7C DTSTART;TZID=Asia/Taipei:20250506T152000 DTEND;TZID=Asia/Taipei:20250506T165000 DESCRIPTION:Since the introduction of phased array in 1905 by Karl Braun\, a Nobel Laureate\, array signal processing has advanced significantly over the past century. The era of adaptive array was started by Jack Capon\, s ignified by his seminal paper in 1969. The Capon beamformer has better res olution and much better interference rejection capability than the data-in dependent beamformer by Karl Braun\, provided that the array steering vect or corresponding to the signal of interest (SOI) and the array covariance matrix is accurately known\, and the SOI is uncorrelated to all other sign als impinging on the array. However\, whenever the knowledge of the SOI st eering vector is imprecise\, the number of data snapshots is scarce\, or t he SOI is correlated with a multipath\, which are often the cases encounte red in practice\, the performance of the Capon beamformer may become worse than that of the data-independent beamformer. For over 50 years\, making the Capon beamformer robust has attracted much interest and tens of thousa nds of papers on robust adaptive array processing have been published in t he literature. To fundamentally overcome the limitations of the Capon fami ly of beamformers\, iterative approaches have been introduced in the recen t literature. Most notably\, the iterative adaptive approach (IAA) was pub lished in 2010 and is shown to possess strong robustness\, and can work we ll under single snapshot and arbitrary array scenarios. We will compare th e nonparametric and user parameter free IAA algorithm with other well-know n algorithms\, including the data-independent beamformer\, the Capon beamf ormer\, the OMP algorithm introduced in the compressed sensing literature\ , as well as the parametric MUSIC and ESPRIT algorithms.\n\nSpeaker(s): Ji an Li \n\nRoom: R105\, Bldg: EECS\, No.101\, Section 2\, Kuang-Fu Road\, Hsinchu\, Taiwan 300044\, R.O.C.\, National Tsing Hua University\, Hsinchu \, T'ai-pei\, Taiwan LOCATION:Room: R105\, Bldg: EECS\, No.101\, Section 2\, Kuang-Fu Road\, Hs inchu\, Taiwan 300044\, R.O.C.\, National Tsing Hua University\, Hsinchu\, T'ai-pei\, Taiwan ORGANIZER:ylueng@ee.nthu.edu.tw SEQUENCE:187 SUMMARY:Over a Century of Array Signal Processing URL;VALUE=URI:https://events.vtools.ieee.org/m/481653 X-ALT-DESC:Description: <br /><p class="MsoNormal"><span lang="EN-US">Since the introduction of phased array in 1905 by Karl Braun\, a Nobel Laureate \, array signal processing has advanced significantly over the past centur y. The era of adaptive array was started by Jack Capon\, signified by his seminal paper in 1969. The Capon beamformer has better resolution and much better interference rejection capability than the data-independent beamfo rmer by Karl Braun\, provided that the array steering vector corresponding to the signal of interest (SOI) and the array covariance matrix is accura tely known\, and the SOI is uncorrelated to all other signals impinging on the array. However\, whenever the knowledge of the SOI steering vector is imprecise\, the number of data snapshots is scarce\, or the SOI is correl ated with a multipath\, which are often the cases encountered in practice\ , the performance of the Capon beamformer may become worse than that of th e data-independent beamformer. For over 50 years\, making the Capon beamfo rmer robust has attracted much interest and tens of thousands of papers on robust adaptive array processing have been published in the literature. T o fundamentally overcome the limitations of the Capon family of beamformer s\, iterative approaches have been introduced in the recent literature. Mo st notably\, the iterative adaptive approach (IAA) was published in 2010 a nd is shown to possess strong robustness\, and can work well under single snapshot and arbitrary array scenarios. We will compare the nonparametric& nbsp\;and user parameter free IAA algorithm with other well-known algorith ms\, including the data-independent beamformer\, the Capon beamformer\, th e OMP algorithm introduced in the compressed sensing literature\, as well as the parametric MUSIC and ESPRIT algorithms.</span></p> END:VEVENT END:VCALENDAR