Infrasound Signal Detection: Re-examining the Component Parts that Makeup Detection Algorithms View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-10-27

AUTHORS

Omar Marcillo , Stephen Arrowsmith , Maurice Charbit , Joshua Carmichael

ABSTRACT

Detecting a Signal Of Interest (SOI) is the first step in many applications of infrasound monitoring. This intuitively simple task is defined as separating out signals from background noise on the basis of the characteristics of observed data; it is, however, deceptively complex. The problem of detecting signals requires multiple processes that are divisible at their highest level into several fundamental tasks. These tasks include (1) defining models for SOIs and noise that properly fit the observations, (2) finding SOIs amongst noise, and (3) estimating parameters of the SOI (e.g., Direction Of Arrival (DOA), Signal-to-Noise Ratio (SNR) and confidence intervals) that can be used for signal characterization. Each of these components involves multiple subcomponents. Here, we explore these three components by examining current infrasound detection algorithms and the assumptions that are made for their operation and exploring and discussing alternative approaches to advance the performance and efficiency of detection operations. This chapter does not address new statistical methods but does offer some insights into the detection problem that may motivate further research. More... »

PAGES

249-271

Book

TITLE

Infrasound Monitoring for Atmospheric Studies

ISBN

978-3-319-75138-2
978-3-319-75140-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-75140-5_7

DOI

http://dx.doi.org/10.1007/978-3-319-75140-5_7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107870629


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Los Alamos National Laboratory", 
          "id": "https://www.grid.ac/institutes/grid.148313.c", 
          "name": [
            "Los Alamos National Laboratory, Los Alamos, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marcillo", 
        "givenName": "Omar", 
        "id": "sg:person.0717447435.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717447435.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Sandia National Laboratories", 
          "id": "https://www.grid.ac/institutes/grid.474520.0", 
          "name": [
            "Sandia National Laboratories, Albuquerque, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Arrowsmith", 
        "givenName": "Stephen", 
        "id": "sg:person.0662422106.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662422106.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Orange (France)", 
          "id": "https://www.grid.ac/institutes/grid.89485.38", 
          "name": [
            "Telecom Paris, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Charbit", 
        "givenName": "Maurice", 
        "id": "sg:person.011061776756.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011061776756.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Los Alamos National Laboratory", 
          "id": "https://www.grid.ac/institutes/grid.148313.c", 
          "name": [
            "Los Alamos National Laboratory, Los Alamos, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Carmichael", 
        "givenName": "Joshua", 
        "id": "sg:person.010645420333.95", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010645420333.95"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1029/2010gl046390", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002387997"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jz067i005p01855", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006892205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/2013jd021084", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008406891"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1190/1.1440453", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008513711"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9780470316849.ch6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009334851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2008jd009822", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009820884"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/2014jd021624", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016117140"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.1971.tb03399.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016608202"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.1971.tb03399.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016608202"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/2014jd022821", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017599173"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2012jc008409", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018198114"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.2011.04975.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019246316"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2002jd003307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023812249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005gl022486", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024918032"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/95gl00468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025891268"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4020-9508-5_2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029965218", 
          "https://doi.org/10.1007/978-1-4020-9508-5_2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4020-9508-5_2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029965218", 
          "https://doi.org/10.1007/978-1-4020-9508-5_2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-0-387-30441-0_81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030685417", 
          "https://doi.org/10.1007/978-0-387-30441-0_81"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-0-387-30441-0_81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030685417", 
          "https://doi.org/10.1007/978-0-387-30441-0_81"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jc078i021p04482", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032288638"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1785/0120060140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032871788"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2011jd016684", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035440458"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/grl.50619", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036506743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.epsl.2011.08.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036561427"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jgrd.50398", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041343115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4236/oja.2014.44020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043048075"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-0-387-30441-0_77", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043913365", 
          "https://doi.org/10.1007/978-0-387-30441-0_77"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-0-387-30441-0_77", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043913365", 
          "https://doi.org/10.1007/978-0-387-30441-0_77"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9574.2012.00530.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044812244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1785/0120080180", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046183963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1962)019<0264:awfnei>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047931922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.2008.03998.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048770345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-246x.2008.03998.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048770345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jvolgeores.2012.09.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049381207"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jz072i009p02403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049437562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jsv.2016.10.027", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049551844"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/physci232079a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053653858", 
          "https://doi.org/10.1038/physci232079a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/physci232079a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053653858", 
          "https://doi.org/10.1038/physci232079a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/physci232079a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053653858", 
          "https://doi.org/10.1038/physci232079a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gji/ggu486", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059637532"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gji/ggu495", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059637539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/79.526899", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061231961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/proc.1969.7278", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061440655"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tac.1974.1100705", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061471419"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tap.1986.1143830", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061494104"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.404049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062355338"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.4789871", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062397978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.4807802", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062400170"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.4809779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062401259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.4954759", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062409756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1306/5d25ca03-16c1-11d7-8645000102c1865d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064943127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1785/0120160125", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083516045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gji/ggy350", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1106310990"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870596", 
          "https://doi.org/10.1007/978-3-319-75140-5_1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870596", 
          "https://doi.org/10.1007/978-3-319-75140-5_1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_13", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870600", 
          "https://doi.org/10.1007/978-3-319-75140-5_13"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_13", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870600", 
          "https://doi.org/10.1007/978-3-319-75140-5_13"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_31", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870620", 
          "https://doi.org/10.1007/978-3-319-75140-5_31"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_31", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870620", 
          "https://doi.org/10.1007/978-3-319-75140-5_31"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_33", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870622", 
          "https://doi.org/10.1007/978-3-319-75140-5_33"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_33", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870622", 
          "https://doi.org/10.1007/978-3-319-75140-5_33"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870628", 
          "https://doi.org/10.1007/978-3-319-75140-5_6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-75140-5_6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107870628", 
          "https://doi.org/10.1007/978-3-319-75140-5_6"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-10-27", 
    "datePublishedReg": "2018-10-27", 
    "description": "Detecting a Signal Of Interest (SOI) is the first step in many applications of infrasound monitoring. This intuitively simple task is defined as separating out signals from background noise on the basis of the characteristics of observed data; it is, however, deceptively complex. The problem of detecting signals requires multiple processes that are divisible at their highest level into several fundamental tasks. These tasks include (1) defining models for SOIs and noise that properly fit the observations, (2) finding SOIs amongst noise, and (3) estimating parameters of the SOI (e.g., Direction Of Arrival (DOA), Signal-to-Noise Ratio (SNR) and confidence intervals) that can be used for signal characterization. Each of these components involves multiple subcomponents. Here, we explore these three components by examining current infrasound detection algorithms and the assumptions that are made for their operation and exploring and discussing alternative approaches to advance the performance and efficiency of detection operations. This chapter does not address new statistical methods but does offer some insights into the detection problem that may motivate further research.", 
    "editor": [
      {
        "familyName": "Le Pichon", 
        "givenName": "Alexis", 
        "type": "Person"
      }, 
      {
        "familyName": "Blanc", 
        "givenName": "Elisabeth", 
        "type": "Person"
      }, 
      {
        "familyName": "Hauchecorne", 
        "givenName": "Alain", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-319-75140-5_7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-319-75138-2", 
        "978-3-319-75140-5"
      ], 
      "name": "Infrasound Monitoring for Atmospheric Studies", 
      "type": "Book"
    }, 
    "name": "Infrasound Signal Detection: Re-examining the Component Parts that Makeup Detection Algorithms", 
    "pagination": "249-271", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-319-75140-5_7"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "f76dd73040d92f3371884f546652e2cf1567c9f94912b2f070001dda63d499d1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107870629"
        ]
      }
    ], 
    "publisher": {
      "location": "Cham", 
      "name": "Springer International Publishing", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-319-75140-5_7", 
      "https://app.dimensions.ai/details/publication/pub.1107870629"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T05:02", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000325_0000000325/records_100815_00000000.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-319-75140-5_7"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75140-5_7'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75140-5_7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75140-5_7'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-75140-5_7'


 

This table displays all metadata directly associated to this object as RDF triples.

264 TRIPLES      23 PREDICATES      77 URIs      19 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-319-75140-5_7 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author N95ee38f5d9d34270bff70c45ac524113
4 schema:citation sg:pub.10.1007/978-0-387-30441-0_77
5 sg:pub.10.1007/978-0-387-30441-0_81
6 sg:pub.10.1007/978-1-4020-9508-5_2
7 sg:pub.10.1007/978-3-319-75140-5_1
8 sg:pub.10.1007/978-3-319-75140-5_13
9 sg:pub.10.1007/978-3-319-75140-5_31
10 sg:pub.10.1007/978-3-319-75140-5_33
11 sg:pub.10.1007/978-3-319-75140-5_6
12 sg:pub.10.1038/physci232079a0
13 https://doi.org/10.1002/2013jd021084
14 https://doi.org/10.1002/2014jd021624
15 https://doi.org/10.1002/2014jd022821
16 https://doi.org/10.1002/9780470316849.ch6
17 https://doi.org/10.1002/grl.50619
18 https://doi.org/10.1002/jgrd.50398
19 https://doi.org/10.1016/j.epsl.2011.08.027
20 https://doi.org/10.1016/j.jsv.2016.10.027
21 https://doi.org/10.1016/j.jvolgeores.2012.09.002
22 https://doi.org/10.1029/2002jd003307
23 https://doi.org/10.1029/2005gl022486
24 https://doi.org/10.1029/2008jd009822
25 https://doi.org/10.1029/2010gl046390
26 https://doi.org/10.1029/2011jd016684
27 https://doi.org/10.1029/2012jc008409
28 https://doi.org/10.1029/95gl00468
29 https://doi.org/10.1029/jc078i021p04482
30 https://doi.org/10.1029/jz067i005p01855
31 https://doi.org/10.1029/jz072i009p02403
32 https://doi.org/10.1093/gji/ggu486
33 https://doi.org/10.1093/gji/ggu495
34 https://doi.org/10.1093/gji/ggy350
35 https://doi.org/10.1109/79.526899
36 https://doi.org/10.1109/proc.1969.7278
37 https://doi.org/10.1109/tac.1974.1100705
38 https://doi.org/10.1109/tap.1986.1143830
39 https://doi.org/10.1111/j.1365-246x.1971.tb03399.x
40 https://doi.org/10.1111/j.1365-246x.2008.03998.x
41 https://doi.org/10.1111/j.1365-246x.2011.04975.x
42 https://doi.org/10.1111/j.1467-9574.2012.00530.x
43 https://doi.org/10.1121/1.404049
44 https://doi.org/10.1121/1.4789871
45 https://doi.org/10.1121/1.4807802
46 https://doi.org/10.1121/1.4809779
47 https://doi.org/10.1121/1.4954759
48 https://doi.org/10.1175/1520-0469(1962)019<0264:awfnei>2.0.co;2
49 https://doi.org/10.1190/1.1440453
50 https://doi.org/10.1306/5d25ca03-16c1-11d7-8645000102c1865d
51 https://doi.org/10.1785/0120060140
52 https://doi.org/10.1785/0120080180
53 https://doi.org/10.1785/0120160125
54 https://doi.org/10.4236/oja.2014.44020
55 schema:datePublished 2018-10-27
56 schema:datePublishedReg 2018-10-27
57 schema:description Detecting a Signal Of Interest (SOI) is the first step in many applications of infrasound monitoring. This intuitively simple task is defined as separating out signals from background noise on the basis of the characteristics of observed data; it is, however, deceptively complex. The problem of detecting signals requires multiple processes that are divisible at their highest level into several fundamental tasks. These tasks include (1) defining models for SOIs and noise that properly fit the observations, (2) finding SOIs amongst noise, and (3) estimating parameters of the SOI (e.g., Direction Of Arrival (DOA), Signal-to-Noise Ratio (SNR) and confidence intervals) that can be used for signal characterization. Each of these components involves multiple subcomponents. Here, we explore these three components by examining current infrasound detection algorithms and the assumptions that are made for their operation and exploring and discussing alternative approaches to advance the performance and efficiency of detection operations. This chapter does not address new statistical methods but does offer some insights into the detection problem that may motivate further research.
58 schema:editor N060ac430167e4327986a52c527691676
59 schema:genre chapter
60 schema:inLanguage en
61 schema:isAccessibleForFree false
62 schema:isPartOf N5393a3fe6edd4fb2b9b4d260f40024f2
63 schema:name Infrasound Signal Detection: Re-examining the Component Parts that Makeup Detection Algorithms
64 schema:pagination 249-271
65 schema:productId N41031719dfc1460fa49cc9042880059a
66 N6f25e180bd5542cf85c234a7ab8b6db2
67 Nbb28351c41cc40988a89929de57c5558
68 schema:publisher N6f01a0d246b54aa78f18a64941dd1907
69 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870629
70 https://doi.org/10.1007/978-3-319-75140-5_7
71 schema:sdDatePublished 2019-04-16T05:02
72 schema:sdLicense https://scigraph.springernature.com/explorer/license/
73 schema:sdPublisher N0bcbde9af33d4ccca4174ac7a2c283af
74 schema:url https://link.springer.com/10.1007%2F978-3-319-75140-5_7
75 sgo:license sg:explorer/license/
76 sgo:sdDataset chapters
77 rdf:type schema:Chapter
78 N060ac430167e4327986a52c527691676 rdf:first N459ff99cbd534677a6ffc1bb33c64dde
79 rdf:rest Ncd760b00358e421f8bf2d99027ae493d
80 N07e7d3788fd2480e968bf435f46f9e48 schema:familyName Blanc
81 schema:givenName Elisabeth
82 rdf:type schema:Person
83 N0bcbde9af33d4ccca4174ac7a2c283af schema:name Springer Nature - SN SciGraph project
84 rdf:type schema:Organization
85 N41031719dfc1460fa49cc9042880059a schema:name doi
86 schema:value 10.1007/978-3-319-75140-5_7
87 rdf:type schema:PropertyValue
88 N44913256959b4b638820b333bbc246cb rdf:first sg:person.0662422106.22
89 rdf:rest Ne775442ec2d543e9b5092d021f6fdb4b
90 N459ff99cbd534677a6ffc1bb33c64dde schema:familyName Le Pichon
91 schema:givenName Alexis
92 rdf:type schema:Person
93 N5393a3fe6edd4fb2b9b4d260f40024f2 schema:isbn 978-3-319-75138-2
94 978-3-319-75140-5
95 schema:name Infrasound Monitoring for Atmospheric Studies
96 rdf:type schema:Book
97 N6ab51e6943d944a1bd34efade4c11275 rdf:first sg:person.010645420333.95
98 rdf:rest rdf:nil
99 N6f01a0d246b54aa78f18a64941dd1907 schema:location Cham
100 schema:name Springer International Publishing
101 rdf:type schema:Organisation
102 N6f25e180bd5542cf85c234a7ab8b6db2 schema:name dimensions_id
103 schema:value pub.1107870629
104 rdf:type schema:PropertyValue
105 N8277bc5fb89b4f2a9a4d34dcae283496 schema:familyName Hauchecorne
106 schema:givenName Alain
107 rdf:type schema:Person
108 N95ee38f5d9d34270bff70c45ac524113 rdf:first sg:person.0717447435.58
109 rdf:rest N44913256959b4b638820b333bbc246cb
110 Nbb28351c41cc40988a89929de57c5558 schema:name readcube_id
111 schema:value f76dd73040d92f3371884f546652e2cf1567c9f94912b2f070001dda63d499d1
112 rdf:type schema:PropertyValue
113 Ncd760b00358e421f8bf2d99027ae493d rdf:first N07e7d3788fd2480e968bf435f46f9e48
114 rdf:rest Ne63497f16f604e60b1bbb0f386423acb
115 Ne63497f16f604e60b1bbb0f386423acb rdf:first N8277bc5fb89b4f2a9a4d34dcae283496
116 rdf:rest rdf:nil
117 Ne775442ec2d543e9b5092d021f6fdb4b rdf:first sg:person.011061776756.50
118 rdf:rest N6ab51e6943d944a1bd34efade4c11275
119 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
120 schema:name Mathematical Sciences
121 rdf:type schema:DefinedTerm
122 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
123 schema:name Statistics
124 rdf:type schema:DefinedTerm
125 sg:person.010645420333.95 schema:affiliation https://www.grid.ac/institutes/grid.148313.c
126 schema:familyName Carmichael
127 schema:givenName Joshua
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010645420333.95
129 rdf:type schema:Person
130 sg:person.011061776756.50 schema:affiliation https://www.grid.ac/institutes/grid.89485.38
131 schema:familyName Charbit
132 schema:givenName Maurice
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011061776756.50
134 rdf:type schema:Person
135 sg:person.0662422106.22 schema:affiliation https://www.grid.ac/institutes/grid.474520.0
136 schema:familyName Arrowsmith
137 schema:givenName Stephen
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662422106.22
139 rdf:type schema:Person
140 sg:person.0717447435.58 schema:affiliation https://www.grid.ac/institutes/grid.148313.c
141 schema:familyName Marcillo
142 schema:givenName Omar
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717447435.58
144 rdf:type schema:Person
145 sg:pub.10.1007/978-0-387-30441-0_77 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043913365
146 https://doi.org/10.1007/978-0-387-30441-0_77
147 rdf:type schema:CreativeWork
148 sg:pub.10.1007/978-0-387-30441-0_81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030685417
149 https://doi.org/10.1007/978-0-387-30441-0_81
150 rdf:type schema:CreativeWork
151 sg:pub.10.1007/978-1-4020-9508-5_2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029965218
152 https://doi.org/10.1007/978-1-4020-9508-5_2
153 rdf:type schema:CreativeWork
154 sg:pub.10.1007/978-3-319-75140-5_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870596
155 https://doi.org/10.1007/978-3-319-75140-5_1
156 rdf:type schema:CreativeWork
157 sg:pub.10.1007/978-3-319-75140-5_13 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870600
158 https://doi.org/10.1007/978-3-319-75140-5_13
159 rdf:type schema:CreativeWork
160 sg:pub.10.1007/978-3-319-75140-5_31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870620
161 https://doi.org/10.1007/978-3-319-75140-5_31
162 rdf:type schema:CreativeWork
163 sg:pub.10.1007/978-3-319-75140-5_33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870622
164 https://doi.org/10.1007/978-3-319-75140-5_33
165 rdf:type schema:CreativeWork
166 sg:pub.10.1007/978-3-319-75140-5_6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107870628
167 https://doi.org/10.1007/978-3-319-75140-5_6
168 rdf:type schema:CreativeWork
169 sg:pub.10.1038/physci232079a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053653858
170 https://doi.org/10.1038/physci232079a0
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1002/2013jd021084 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008406891
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1002/2014jd021624 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016117140
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1002/2014jd022821 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017599173
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1002/9780470316849.ch6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009334851
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1002/grl.50619 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036506743
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1002/jgrd.50398 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041343115
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1016/j.epsl.2011.08.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036561427
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1016/j.jsv.2016.10.027 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049551844
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1016/j.jvolgeores.2012.09.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049381207
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1029/2002jd003307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023812249
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1029/2005gl022486 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024918032
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1029/2008jd009822 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009820884
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1029/2010gl046390 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002387997
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1029/2011jd016684 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035440458
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1029/2012jc008409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018198114
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1029/95gl00468 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025891268
203 rdf:type schema:CreativeWork
204 https://doi.org/10.1029/jc078i021p04482 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032288638
205 rdf:type schema:CreativeWork
206 https://doi.org/10.1029/jz067i005p01855 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006892205
207 rdf:type schema:CreativeWork
208 https://doi.org/10.1029/jz072i009p02403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049437562
209 rdf:type schema:CreativeWork
210 https://doi.org/10.1093/gji/ggu486 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059637532
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1093/gji/ggu495 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059637539
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1093/gji/ggy350 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106310990
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1109/79.526899 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061231961
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1109/proc.1969.7278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061440655
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1109/tac.1974.1100705 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061471419
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1109/tap.1986.1143830 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061494104
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1111/j.1365-246x.1971.tb03399.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016608202
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1111/j.1365-246x.2008.03998.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048770345
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1111/j.1365-246x.2011.04975.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1019246316
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1111/j.1467-9574.2012.00530.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1044812244
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1121/1.404049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062355338
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1121/1.4789871 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062397978
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1121/1.4807802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062400170
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1121/1.4809779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062401259
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1121/1.4954759 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062409756
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1175/1520-0469(1962)019<0264:awfnei>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047931922
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1190/1.1440453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008513711
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1306/5d25ca03-16c1-11d7-8645000102c1865d schema:sameAs https://app.dimensions.ai/details/publication/pub.1064943127
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1785/0120060140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032871788
249 rdf:type schema:CreativeWork
250 https://doi.org/10.1785/0120080180 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046183963
251 rdf:type schema:CreativeWork
252 https://doi.org/10.1785/0120160125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083516045
253 rdf:type schema:CreativeWork
254 https://doi.org/10.4236/oja.2014.44020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043048075
255 rdf:type schema:CreativeWork
256 https://www.grid.ac/institutes/grid.148313.c schema:alternateName Los Alamos National Laboratory
257 schema:name Los Alamos National Laboratory, Los Alamos, USA
258 rdf:type schema:Organization
259 https://www.grid.ac/institutes/grid.474520.0 schema:alternateName Sandia National Laboratories
260 schema:name Sandia National Laboratories, Albuquerque, USA
261 rdf:type schema:Organization
262 https://www.grid.ac/institutes/grid.89485.38 schema:alternateName Orange (France)
263 schema:name Telecom Paris, Paris, France
264 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...