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160325s2015 a 001c chi
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▼a 9783319175560:
▼c \(원화)68439 -
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▼a 2191-5423
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▼a 248023
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▼d 248023 -
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▼a Sullivan, Edmund J.
-
245
▼a Model-Based Processing for Underwater Acoustic Arrays:/
▼d Edmund J. Sullivan. -
260
▼a [cham]:
▼b Springer,
▼c 2015. -
300
▼a x,113 p.:
▼b ill.;
▼c 24 cm. -
440
▼a Springer briefs in physics
-
500
▼a Includes index
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520
▼a This monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Thirdly, such a unification provides a formal means of quantifying the performance improvement. The term model-based will be strictly defined as the use of physics-based models as a means of introducing a priori information. This leads naturally to viewing the method as a Bayesian processor. Short expositions of estimation theory and acoustic array theory are presented, followed by a presentation of the Kalman filter in its recursive estimator form. Examples of applications to localization, bearing estimation, range estimation and model parameter estimation are provided along with experimental results verifying the method. The book is sufficiently self-contained to serve as a guide for the application of model-based array processing for the practicing engineer
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653
▼a Underwater
▼a acoustics
▼a Mathematical
▼a models -
990
▼a 김희원
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▼a 단행본
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▼a 620.25
▼b S949m
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상세정보
Model-Based Processing for Underwater Acoustic Arrays
QR코드| 자료유형 : | 단행본 |
|---|---|
| ISBN : | 9783319175560: |
| ISSN : | 2191-5423 |
| 개인저자 : | Sullivan, Edmund J. |
| 서명/저자사항 : | Model-Based Processing for Underwater Acoustic Arrays:/ Edmund J. Sullivan. |
| 발행사항 : | [cham]: Springer, 2015. |
| 형태사항 : | x,113 p.: ill.; 24 cm. |
| 총서사항 : | Springer briefs in physics |
| 일반주기 : | Includes index |
| 요약 : | This monograph presents a unified approach to model-based processing for underwater acoustic arrays. The use of physical models in passive array processing is not a new idea, but it has been used on a case-by-case basis, and as such, lacks any unifying structure. This work views all such processing methods as estimation procedures, which then can be unified by treating them all as a form of joint estimation based on a Kalman-type recursive processor, which can be recursive either in space or time, depending on the application. This is done for three reasons. First, the Kalman filter provides a natural framework for the inclusion of physical models in a processing scheme. Second, it allows poorly known model parameters to be jointly estimated along with the quantities of interest. This is important, since in certain areas of array processing already in use, such as those based on matched-field processing, the so-called mismatch problem either degrades performance or, indeed, prevents any solution at all. Thirdly, such a unification provides a formal means of quantifying the performance improvement. The term model-based will be strictly defined as the use of physics-based models as a means of introducing a priori information. This leads naturally to viewing the method as a Bayesian processor. Short expositions of estimation theory and acoustic array theory are presented, followed by a presentation of the Kalman filter in its recursive estimator form. Examples of applications to localization, bearing estimation, range estimation and model parameter estimation are provided along with experimental results verifying the method. The book is sufficiently self-contained to serve as a guide for the application of model-based array processing for the practicing engineer |
| 분류기호 : | 620.25 |
| 언어 | 중국어 |
예약
- 1. 예약현황은 홈페이지 로그인 후 예약 페이지에 확인 가능합니다.
- 2. 도착 통보된 예약자료 대출을 원하지 않는 경우에는 예약 현황에서 취소할 수 있습니다.
- 3. 기타 문의사항은 도서관에 문의 바랍니다.
무인예약대출
- 1. 무인예약대출 현황은 홈페이지 로그인 후 무인예약대출 페이지에 확인 가능합니다.
- 2. 무인예약대출자료 대출을 원하지 않는 경우에는 무인예약대출 페이지에서 신청 또는 접수상태인 경우만 취소할 수 있습니다.
- 3. 희망대출일은 신청일로부터 최대 1주일 까지 가능합니다.
- 4. 희망대출일을 선택하지 않은 경우 대출대기 통보 후 1주일까지 기기에서 대출가능합니다.
- 5. 기타 문의사항은 도서관에 문의 바랍니다.
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