Unconditional maximum likelihood approach for localization of near-field sources in 3-D space

Nihat Kabaog̃lu; Hakan A. Çirpan; Selçuk Paker

Unconditional maximum likelihood approach for localization of near-field sources in 3-D space

Nihat Kabaog̃lu^*
, Hakan A. Çirpan
, Selçuk Paker

^*Bu çalışma için yazışmadan sorumlu yazar

Elektronik ve Hab.Müh.Bölümü

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

9 Atıf (Scopus)

Özet

Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ratios, we propose unconditional ML (UML) method for estimating azimuth, elevation and range parameters of near-field sources in 3-D space in this paper. Besides these superiorities, stability, asymptotic unbiasedness, asymptotic minimum variance properties are motivated the application of ML approach. Despite these advantages, ML estimator has computational complexity. Fortunately, this problem can be tackled by the application of Expectation/Maximization (EM) iterative algorithm which converts the multidimensional search problem to one dimensional parallel search problems in order to prevent computational complexity.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology
Sayfalar	233-237
Sayfa sayısı	5
Yayın durumu	Yayınlandı - 2004
Etkinlik	Fourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004 - Rome, Italy Süre: 18 Ara 2004 → 21 Ara 2004

Yayın serisi

Adı	Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	Fourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004
Ülke/Bölge	Italy
Şehir	Rome
Periyot	18/12/04 → 21/12/04

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kabaog̃lu, N., Çirpan, H. A., & Paker, S. (2004). Unconditional maximum likelihood approach for localization of near-field sources in 3-D space. In Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology (pp. 233-237). (Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004).

Kabaog̃lu, Nihat ; Çirpan, Hakan A. ; Paker, Selçuk. / Unconditional maximum likelihood approach for localization of near-field sources in 3-D space. Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology. 2004. pp. 233-237 (Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004).

@inproceedings{a59150bfbc9242129de197863c134dab,

title = "Unconditional maximum likelihood approach for localization of near-field sources in 3-D space",

abstract = "Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ratios, we propose unconditional ML (UML) method for estimating azimuth, elevation and range parameters of near-field sources in 3-D space in this paper. Besides these superiorities, stability, asymptotic unbiasedness, asymptotic minimum variance properties are motivated the application of ML approach. Despite these advantages, ML estimator has computational complexity. Fortunately, this problem can be tackled by the application of Expectation/Maximization (EM) iterative algorithm which converts the multidimensional search problem to one dimensional parallel search problems in order to prevent computational complexity.",

author = "Nihat Kabao{\~g}lu and {\c C}irpan, \{Hakan A.\} and Sel{\c c}uk Paker",

year = "2004",

language = "English",

isbn = "0780386892",

series = "Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004",

pages = "233--237",

booktitle = "Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology",

note = "Fourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004 ; Conference date: 18-12-2004 Through 21-12-2004",

}

Kabaog̃lu, N, Çirpan, HA & Paker, S 2004, Unconditional maximum likelihood approach for localization of near-field sources in 3-D space. in Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology. Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004, pp. 233-237, Fourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004, Rome, Italy, 18/12/04.

Unconditional maximum likelihood approach for localization of near-field sources in 3-D space. / Kabaog̃lu, Nihat; Çirpan, Hakan A.; Paker, Selçuk.
Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology. 2004. p. 233-237 (Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Unconditional maximum likelihood approach for localization of near-field sources in 3-D space

AU - Kabaog̃lu, Nihat

AU - Çirpan, Hakan A.

AU - Paker, Selçuk

PY - 2004

Y1 - 2004

N2 - Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ratios, we propose unconditional ML (UML) method for estimating azimuth, elevation and range parameters of near-field sources in 3-D space in this paper. Besides these superiorities, stability, asymptotic unbiasedness, asymptotic minimum variance properties are motivated the application of ML approach. Despite these advantages, ML estimator has computational complexity. Fortunately, this problem can be tackled by the application of Expectation/Maximization (EM) iterative algorithm which converts the multidimensional search problem to one dimensional parallel search problems in order to prevent computational complexity.

AB - Since maximum likelihood (ML) approaches have better resolution performance than the conventional localization methods in the presence of less number and highly correlated source signal samples and low signal to noise ratios, we propose unconditional ML (UML) method for estimating azimuth, elevation and range parameters of near-field sources in 3-D space in this paper. Besides these superiorities, stability, asymptotic unbiasedness, asymptotic minimum variance properties are motivated the application of ML approach. Despite these advantages, ML estimator has computational complexity. Fortunately, this problem can be tackled by the application of Expectation/Maximization (EM) iterative algorithm which converts the multidimensional search problem to one dimensional parallel search problems in order to prevent computational complexity.

UR - https://www.scopus.com/pages/publications/21544453326

M3 - Conference contribution

AN - SCOPUS:21544453326

SN - 0780386892

T3 - Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004

SP - 233

EP - 237

BT - Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology

T2 - Fourth IEEE International Symposium on Signal processing and Information Technology, ISSPIT 2004

Y2 - 18 December 2004 through 21 December 2004

ER -

Kabaog̃lu N, Çirpan HA, Paker S. Unconditional maximum likelihood approach for localization of near-field sources in 3-D space. In Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology. 2004. p. 233-237. (Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004).

Unconditional maximum likelihood approach for localization of near-field sources in 3-D space

Özet

Yayın serisi

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