Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments
Model based array parametric direction nding algorithms are among the most accurate techniques known of determining the direction to a source. The deterministic 1 maximum likelihood (DML) algorithm is one such technique that determines the direction of a set of narrow-band sources by tting the recei...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Text |
Language: | English |
Subjects: | |
Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.8578 http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf |
id |
ftciteseerx:oai:CiteSeerX.psu:10.1.1.33.8578 |
---|---|
record_format |
openpolar |
spelling |
ftciteseerx:oai:CiteSeerX.psu:10.1.1.33.8578 2023-05-15T16:01:16+02:00 Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments Mitre Paper Stanley W. Pawlukiewicz The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.8578 http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.8578 http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf text ftciteseerx 2016-09-04T00:39:11Z Model based array parametric direction nding algorithms are among the most accurate techniques known of determining the direction to a source. The deterministic 1 maximum likelihood (DML) algorithm is one such technique that determines the direction of a set of narrow-band sources by tting the received sensor data to a statistical model. For many algorithms such as DML, the sensor data is modeled as a uniform and continuous spatial background with a set of discrete point sources. When the assumed model is a good characterization of the received data, the model is said to be matched. In practice there is often, if not always, some degree of model mismatch encountered with real data because models are inherently idealized constructions. The eects of mismatch on parameter estimation algorithms is an important issue to system designers. In this paper we specically examine model mismatch in DML when the background noise is spatially correlated and unknown. In correlated background noi. Text DML Unknown |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
ftciteseerx |
language |
English |
description |
Model based array parametric direction nding algorithms are among the most accurate techniques known of determining the direction to a source. The deterministic 1 maximum likelihood (DML) algorithm is one such technique that determines the direction of a set of narrow-band sources by tting the received sensor data to a statistical model. For many algorithms such as DML, the sensor data is modeled as a uniform and continuous spatial background with a set of discrete point sources. When the assumed model is a good characterization of the received data, the model is said to be matched. In practice there is often, if not always, some degree of model mismatch encountered with real data because models are inherently idealized constructions. The eects of mismatch on parameter estimation algorithms is an important issue to system designers. In this paper we specically examine model mismatch in DML when the background noise is spatially correlated and unknown. In correlated background noi. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Mitre Paper Stanley W. Pawlukiewicz |
spellingShingle |
Mitre Paper Stanley W. Pawlukiewicz Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
author_facet |
Mitre Paper Stanley W. Pawlukiewicz |
author_sort |
Mitre Paper |
title |
Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
title_short |
Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
title_full |
Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
title_fullStr |
Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
title_full_unstemmed |
Pseudo Bounds for Deterministic Maximum Likelihood (DML) Direction Finding Errors in Correlated Noise Environments |
title_sort |
pseudo bounds for deterministic maximum likelihood (dml) direction finding errors in correlated noise environments |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.8578 http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf |
genre |
DML |
genre_facet |
DML |
op_source |
http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.8578 http://www-i.mitre.org/centers/wc3/asto/docs/Papers/Technical/DFerrors.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
_version_ |
1766397200626089984 |