Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Philipp Heidenreich , Abdelhak M. Zoubir

ABSTRACT

Direction-of-arrival (DOA) estimation of two targets with a single snapshot plays an important role in many practically relevant scenarios in automotive radar for driver assistance systems. Conventional Fourier-based methods cannot resolve closely spaced targets, and high-resolution methods are required. Thus, we consider the maximum likelihood DOA estimator, which is applicable with a single snapshot. To reduce the computational burden, we propose a grid search procedure with a simplified objective function. The required projection operators are pre-calculated off-line and stored. To save storage space, we further propose a rotational shift of the field of view such that the relevant angular sector, which has to be evaluated, is centered with respect to the broadside. The final estimates are obtained using a quadratic interpolation. An example is presented to demonstrate the proposed method. Also, results obtained with experimental data from a typical application in automotive radar are shown. More... »

PAGES

3-18

Book

TITLE

Smart Mobile In-Vehicle Systems

ISBN

978-1-4614-9119-4
978-1-4614-9120-0

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4614-9120-0_1

DOI

http://dx.doi.org/10.1007/978-1-4614-9120-0_1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050256739


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "ADC Automotive Distance Control Systems GmbH, Peter-Dornier-Str. 10, 88131\u00a0Lindau, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Heidenreich", 
        "givenName": "Philipp", 
        "id": "sg:person.013707562743.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013707562743.99"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Darmstadt", 
          "id": "https://www.grid.ac/institutes/grid.6546.1", 
          "name": [
            "Signal Processing Group, Technische Universit\u00e4t Darmstadt, Merckstr. 25, 64283\u00a0Darmstadt, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zoubir", 
        "givenName": "Abdelhak M.", 
        "id": "sg:person.013316510015.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013316510015.38"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0024-3795(80)90241-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032568453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/29.17496", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061144305"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/29.17564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061144363"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/29.7543", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061144755"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/7.599338", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061215133"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/78.382406", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061229087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/78.839978", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061231170"
        ], 
        "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/msp.2009.932618", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061423280"
        ], 
        "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/10.1002/0471221104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098661263"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/0471221104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098661263"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014", 
    "datePublishedReg": "2014-01-01", 
    "description": "Direction-of-arrival (DOA) estimation of two targets with a single snapshot plays an important role in many practically relevant scenarios in automotive radar for driver assistance systems. Conventional Fourier-based methods cannot resolve closely spaced targets, and high-resolution methods are required. Thus, we consider the maximum likelihood DOA estimator, which is applicable with a single snapshot. To reduce the computational burden, we propose a grid search procedure with a simplified objective function. The required projection operators are pre-calculated off-line and stored. To save storage space, we further propose a rotational shift of the field of view such that the relevant angular sector, which has to be evaluated, is centered with respect to the broadside. The final estimates are obtained using a quadratic interpolation. An example is presented to demonstrate the proposed method. Also, results obtained with experimental data from a typical application in automotive radar are shown.", 
    "editor": [
      {
        "familyName": "Schmidt", 
        "givenName": "Gerhard", 
        "type": "Person"
      }, 
      {
        "familyName": "Abut", 
        "givenName": "Huseyin", 
        "type": "Person"
      }, 
      {
        "familyName": "Takeda", 
        "givenName": "Kazuya", 
        "type": "Person"
      }, 
      {
        "familyName": "Hansen", 
        "givenName": "John H.L.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4614-9120-0_1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-4614-9119-4", 
        "978-1-4614-9120-0"
      ], 
      "name": "Smart Mobile In-Vehicle Systems", 
      "type": "Book"
    }, 
    "name": "Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar", 
    "pagination": "3-18", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4614-9120-0_1"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ef68b4e5966cb4f540015ad3e306b7f6812459ad4f06c12541da8da4a8c2e85e"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1050256739"
        ]
      }
    ], 
    "publisher": {
      "location": "New York, NY", 
      "name": "Springer New York", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4614-9120-0_1", 
      "https://app.dimensions.ai/details/publication/pub.1050256739"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T12:35", 
    "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/v90/0000000001_0000000264/records_8663_00000274.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-1-4614-9120-0_1"
  }
]
 

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.10.1007/978-1-4614-9120-0_1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4614-9120-0_1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4614-9120-0_1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4614-9120-0_1'


 

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

122 TRIPLES      23 PREDICATES      38 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4614-9120-0_1 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N286d4f8ceb7c425a96f13c17c18531b1
4 schema:citation https://doi.org/10.1002/0471221104
5 https://doi.org/10.1016/0024-3795(80)90241-4
6 https://doi.org/10.1109/29.17496
7 https://doi.org/10.1109/29.17564
8 https://doi.org/10.1109/29.7543
9 https://doi.org/10.1109/7.599338
10 https://doi.org/10.1109/78.382406
11 https://doi.org/10.1109/78.839978
12 https://doi.org/10.1109/79.526899
13 https://doi.org/10.1109/msp.2009.932618
14 https://doi.org/10.1109/tap.1986.1143830
15 schema:datePublished 2014
16 schema:datePublishedReg 2014-01-01
17 schema:description Direction-of-arrival (DOA) estimation of two targets with a single snapshot plays an important role in many practically relevant scenarios in automotive radar for driver assistance systems. Conventional Fourier-based methods cannot resolve closely spaced targets, and high-resolution methods are required. Thus, we consider the maximum likelihood DOA estimator, which is applicable with a single snapshot. To reduce the computational burden, we propose a grid search procedure with a simplified objective function. The required projection operators are pre-calculated off-line and stored. To save storage space, we further propose a rotational shift of the field of view such that the relevant angular sector, which has to be evaluated, is centered with respect to the broadside. The final estimates are obtained using a quadratic interpolation. An example is presented to demonstrate the proposed method. Also, results obtained with experimental data from a typical application in automotive radar are shown.
18 schema:editor N75d8852747a64948984893f1de3496f7
19 schema:genre chapter
20 schema:inLanguage en
21 schema:isAccessibleForFree false
22 schema:isPartOf Ne49d0b507762466291346dcf2493b3c0
23 schema:name Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar
24 schema:pagination 3-18
25 schema:productId N0aef1ed711314601ab0d66a54ddd28a0
26 N9b0f49b1f82b43068ca24f8fba0c4cbe
27 Nc4d85940ca184e22a33c5f0af0462d02
28 schema:publisher Ndeddf30ebfb4488f94733463cd337002
29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050256739
30 https://doi.org/10.1007/978-1-4614-9120-0_1
31 schema:sdDatePublished 2019-04-15T12:35
32 schema:sdLicense https://scigraph.springernature.com/explorer/license/
33 schema:sdPublisher Nc22ae0d92b3d45b080fde58da939bbe2
34 schema:url http://link.springer.com/10.1007/978-1-4614-9120-0_1
35 sgo:license sg:explorer/license/
36 sgo:sdDataset chapters
37 rdf:type schema:Chapter
38 N0aef1ed711314601ab0d66a54ddd28a0 schema:name readcube_id
39 schema:value ef68b4e5966cb4f540015ad3e306b7f6812459ad4f06c12541da8da4a8c2e85e
40 rdf:type schema:PropertyValue
41 N0ece95fc080c4e9c9454bb5a1708c9b9 schema:familyName Schmidt
42 schema:givenName Gerhard
43 rdf:type schema:Person
44 N130fc9faca21449c9555717ba0de2349 schema:name ADC Automotive Distance Control Systems GmbH, Peter-Dornier-Str. 10, 88131 Lindau, Germany
45 rdf:type schema:Organization
46 N286d4f8ceb7c425a96f13c17c18531b1 rdf:first sg:person.013707562743.99
47 rdf:rest N6480bcc5b40949d6a17cde440cee872e
48 N4c50e8fec0eb41c396830b8d4749c8b4 schema:familyName Hansen
49 schema:givenName John H.L.
50 rdf:type schema:Person
51 N56230db77edc48a1b08f3054f2cd390e rdf:first Nb0766cf2f163487e9772e7703dd02eeb
52 rdf:rest Nd2df670bad2c4822b4765303bb0eec12
53 N6480bcc5b40949d6a17cde440cee872e rdf:first sg:person.013316510015.38
54 rdf:rest rdf:nil
55 N75d8852747a64948984893f1de3496f7 rdf:first N0ece95fc080c4e9c9454bb5a1708c9b9
56 rdf:rest N992ec34f2f7e42868f96e49575fd4506
57 N7b94c7761be244e1969b0a38a6ba04ac schema:familyName Abut
58 schema:givenName Huseyin
59 rdf:type schema:Person
60 N992ec34f2f7e42868f96e49575fd4506 rdf:first N7b94c7761be244e1969b0a38a6ba04ac
61 rdf:rest N56230db77edc48a1b08f3054f2cd390e
62 N9b0f49b1f82b43068ca24f8fba0c4cbe schema:name doi
63 schema:value 10.1007/978-1-4614-9120-0_1
64 rdf:type schema:PropertyValue
65 Nb0766cf2f163487e9772e7703dd02eeb schema:familyName Takeda
66 schema:givenName Kazuya
67 rdf:type schema:Person
68 Nc22ae0d92b3d45b080fde58da939bbe2 schema:name Springer Nature - SN SciGraph project
69 rdf:type schema:Organization
70 Nc4d85940ca184e22a33c5f0af0462d02 schema:name dimensions_id
71 schema:value pub.1050256739
72 rdf:type schema:PropertyValue
73 Nd2df670bad2c4822b4765303bb0eec12 rdf:first N4c50e8fec0eb41c396830b8d4749c8b4
74 rdf:rest rdf:nil
75 Ndeddf30ebfb4488f94733463cd337002 schema:location New York, NY
76 schema:name Springer New York
77 rdf:type schema:Organisation
78 Ne49d0b507762466291346dcf2493b3c0 schema:isbn 978-1-4614-9119-4
79 978-1-4614-9120-0
80 schema:name Smart Mobile In-Vehicle Systems
81 rdf:type schema:Book
82 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
83 schema:name Information and Computing Sciences
84 rdf:type schema:DefinedTerm
85 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
86 schema:name Artificial Intelligence and Image Processing
87 rdf:type schema:DefinedTerm
88 sg:person.013316510015.38 schema:affiliation https://www.grid.ac/institutes/grid.6546.1
89 schema:familyName Zoubir
90 schema:givenName Abdelhak M.
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013316510015.38
92 rdf:type schema:Person
93 sg:person.013707562743.99 schema:affiliation N130fc9faca21449c9555717ba0de2349
94 schema:familyName Heidenreich
95 schema:givenName Philipp
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013707562743.99
97 rdf:type schema:Person
98 https://doi.org/10.1002/0471221104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098661263
99 rdf:type schema:CreativeWork
100 https://doi.org/10.1016/0024-3795(80)90241-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032568453
101 rdf:type schema:CreativeWork
102 https://doi.org/10.1109/29.17496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061144305
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1109/29.17564 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061144363
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1109/29.7543 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061144755
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1109/7.599338 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061215133
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1109/78.382406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061229087
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1109/78.839978 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061231170
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1109/79.526899 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061231961
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1109/msp.2009.932618 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061423280
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1109/tap.1986.1143830 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061494104
119 rdf:type schema:CreativeWork
120 https://www.grid.ac/institutes/grid.6546.1 schema:alternateName Technical University of Darmstadt
121 schema:name Signal Processing Group, Technische Universität Darmstadt, Merckstr. 25, 64283 Darmstadt, Germany
122 rdf:type schema:Organization
 




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


...