BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Eastern BEGIN:DAYLIGHT DTSTART:20220313T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20211107T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220121T002741Z UID:754D87E4-96B1-461D-981D-748C02CE2480 DTSTART;TZID=US/Eastern:20220113T173000 DTEND;TZID=US/Eastern:20220113T210000 DESCRIPTION:Modal Array Signal Processing: A Brief Introduction\n\nThe scal ar acoustic pressure sound field obeys the Helmholtz equation. It can be s hown that under certain restrictions\, pressure or particle velocity measu rements on a closed surface can be used to uniquely infer the entire acous tic field. This observation leads to a different beamforming methodology f or volumetric arrays where instead of combining filtered outputs of indivi dual sensors\, the measurements can be used to spatially decompose the arr ay response in terms of an orthonormal basis defined by the array surface resulting in “eigenbeams.” Modal beamforming is then performed by line arly processing over the eigenbeams to realize desired beampatterns. Since the number of modes can be significantly less than the number of sensors there is a computational advantage over classical methods. Additionally\, modal processing offers a layer of abstraction (the “eigenbeams space” ) to accommodate a wide variety of array geometries which simplifies downs tream processing tasks. However\, sensitivities to shape deformation\, suc h as an array in typical oceanic currents may undergo\, are not amenable t o classical error tolerance analysis and novel approaches to "array-healin g" must be explored. To clarify these concepts an example of a moored cyli ndrical array of sensors in a typical ocean environment is shown.\n\nUnder sea Tracking: From Kalman Filters to Particle Flow Filters\n\nAs foreign n avies become increasingly more prolific and more capable and foreign subma rines become quieter\, the US Navy is working to enhance their undersea si tuational awareness capability. The goal is to create a Single Integrated Undersea Picture (SIUP) to monitor large volumes of the ocean. Undersea tr acking has always been challenging due to high densities of dynamically mo ving contacts\, environmental conditions causing shadow zones resulting in intermittent tracks\, low SNR conditions\, non-Gaussian noise\, and non-l inearities in the system and measurement models. Over the years\, a myriad of different contact tracking solutions have been proposed with varying d egrees of success\, starting with simple Kalman filters and most recently particle flow filters. This brief will walk us through the history of sona r tracking algorithms focusing mainly on submarine sonar tracking systems. Variants of the Kalman filter will be discussed along with Multiple Hypot hesis Tests\, Interacting Multiple Models\, Maximum Likelihood Estimators\ , Particle Filters\, and Particle Flow filters. Recent developments in det erministic and stochastic flow models will also be discussed. In numerical experiments\, particle flow filters have been shown to reduce computation al complexity by many orders of magnitude relative to standard particle fi lters or other state-of-the-art algorithms for the same filter accuracy. M oreover\, particle flow filters can reduce the filter errors by many order s of magnitude relative to the extended Kalman filter or other state-of-th e-art algorithms for difficult nonlinear non-Gaussian problems.\n\nSpeaker (s): Dr. Kevin Bongiovanni\, Dr. Ken McPhillips\n\nAgenda: \n5:30 PM - Coc ktails (cash bar)\n\n6:00 PM - Modal Array Signal Processing\n\n6:30 PM - Particle Flow Filters for Tracking\n\n7:00 PM - Dinner*\n\n*Please registe r in advance\; Dinner menu preview is available at www.galleygrille.com\n\ nThe Galley Grille at White's of Westport\, 66 State Road\, Westport\, Mas sachusetts\, United States\, 02790\, Virtual: https://events.vtools.ieee.o rg/m/293930 LOCATION:The Galley Grille at White's of Westport\, 66 State Road\, Westpor t\, Massachusetts\, United States\, 02790\, Virtual: https://events.vtools .ieee.org/m/293930 ORGANIZER:Jason.e.gaudette@ieee.org SEQUENCE:18 SUMMARY:Technical Briefs on Modal Array Signal Processing and Undersea Trac king URL;VALUE=URI:https://events.vtools.ieee.org/m/293930 X-ALT-DESC:Description: <br /><p><strong>Modal Array Signal Processing: A B rief Introduction</strong></p>\n<p>The scalar acoustic pressure sound fiel d obeys the Helmholtz equation. It can be shown that under certain restric tions\, pressure or particle velocity measurements on a closed surface can be used to uniquely infer the entire acoustic field. This observation lea ds to a different beamforming methodology for volumetric arrays where inst ead of combining filtered outputs of individual sensors\, the measurements can be used to spatially decompose the array response in terms of an orth onormal basis defined by the array surface resulting in &ldquo\;eigenbeams .&rdquo\; Modal beamforming is then performed by linearly processing over the eigenbeams to realize desired beampatterns. Since the number of modes can be significantly less than the number of sensors there is a computatio nal advantage over classical methods. Additionally\, modal processing offe rs a layer of abstraction (the &ldquo\;eigenbeams space&rdquo\;) to accomm odate a wide variety of array geometries which simplifies downstream proce ssing tasks. However\, sensitivities to shape deformation\, such as an arr ay in typical oceanic currents may undergo\, are not amenable to classical error tolerance analysis and novel approaches to "array-healing" must be explored. To clarify these concepts an example of a moored cylindrical arr ay of sensors in a typical ocean environment is shown.</p>\n<p><strong>Und ersea Tracking:&nbsp\; From Kalman Filters to Particle Flow Filters</stron g></p>\n<p><span style="font-weight: 400\;">As foreign navies become incre asingly more prolific and more capable and foreign submarines become quiet er\, the US Navy is working to enhance their undersea situational awarenes s capability.&nbsp\; The goal is to create a Single Integrated Undersea Pi cture (SIUP) to monitor large volumes of the ocean. Undersea tracking has always been challenging due to high densities of dynamically moving contac ts\, environmental conditions causing shadow zones resulting in intermitte nt tracks\, low SNR conditions\,&nbsp\; non-Gaussian noise\, and non-linea rities in the system and measurement models.&nbsp\; Over the years\, a myr iad of different contact tracking solutions have been proposed with varyin g degrees of success\, starting with simple Kalman filters and most recent ly particle flow filters.&nbsp\; This brief will walk us through the histo ry of sonar tracking algorithms focusing mainly on submarine sonar trackin g systems. Variants of the Kalman filter will be discussed along with Mult iple Hypothesis Tests\, Interacting Multiple Models\,&nbsp\; Maximum Likel ihood Estimators\, Particle Filters\, and Particle Flow filters.&nbsp\; Re cent developments in deterministic and stochastic flow models will also be discussed.&nbsp\; In numerical experiments\, particle flow filters have b een shown to reduce computational complexity by many orders of magnitude r elative to standard particle filters or other state-of-the-art algorithms for the same filter accuracy. Moreover\, particle flow filters can reduce the filter errors by many orders of magnitude relative to the extended Kal man filter or other state-of-the-art algorithms for difficult nonlinear no n-Gaussian problems.</span></p><br /><br />Agenda: <br /><p>5:30 PM - Cock tails (cash bar)</p>\n<p>6:00 PM - Modal Array Signal Processing</p>\n<p>6 :30 PM - Particle Flow Filters for Tracking</p>\n<p>7:00 PM - Dinner*</p>\ n<p>*Please register in advance\;&nbsp\; Dinner menu preview is available at www.galleygrille.com</p> END:VEVENT END:VCALENDAR