A Propagation Environment Modeling in Foliage
Foliage clutter, which can be very large and mask targets in backscattered signals, is a crucial factor that degrades the performance of target detection, tracking, and recognition. Previous literature has intensively investigated land clutter and sea clutter, whereas foliage clutter is still an ope...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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SpringerOpen
2010-01-01
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Series: | EURASIP Journal on Wireless Communications and Networking |
Online Access: | http://dx.doi.org/10.1155/2010/873070 |
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author | Sherwood W. Samn Jing Liang Qilian Liang |
author_facet | Sherwood W. Samn Jing Liang Qilian Liang |
author_sort | Sherwood W. Samn |
collection | DOAJ |
description | Foliage clutter, which can be very large and mask targets in backscattered signals, is a crucial factor that degrades the performance of target detection, tracking, and recognition. Previous literature has intensively investigated land clutter and sea clutter, whereas foliage clutter is still an open-research area. In this paper, we propose that foliage clutter should be more accurately described by a log-logistic model. On a basis of pragmatic data collected by ultra-wideband (UWB) radars, we analyze two different datasets by means of maximum likelihood (ML) parameter estimation as well as the root mean square error (RMSE) performance. We not only investigate log-logistic model, but also compare it with other popular clutter models, namely, log-normal, Weibull, and Nakagami. It shows that the log-logistic model achieves the smallest standard deviation (STD) error in parameter estimation, as well as the best goodness-of-fit and smallest RMSE for both poor and good foliage clutter signals. |
first_indexed | 2024-04-14T04:28:25Z |
format | Article |
id | doaj.art-5e7fc14a511541c2a7a9f00ea853b83a |
institution | Directory Open Access Journal |
issn | 1687-1472 1687-1499 |
language | English |
last_indexed | 2024-04-14T04:28:25Z |
publishDate | 2010-01-01 |
publisher | SpringerOpen |
record_format | Article |
series | EURASIP Journal on Wireless Communications and Networking |
spelling | doaj.art-5e7fc14a511541c2a7a9f00ea853b83a2022-12-22T02:12:09ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992010-01-01201010.1155/2010/873070A Propagation Environment Modeling in FoliageSherwood W. SamnJing LiangQilian LiangFoliage clutter, which can be very large and mask targets in backscattered signals, is a crucial factor that degrades the performance of target detection, tracking, and recognition. Previous literature has intensively investigated land clutter and sea clutter, whereas foliage clutter is still an open-research area. In this paper, we propose that foliage clutter should be more accurately described by a log-logistic model. On a basis of pragmatic data collected by ultra-wideband (UWB) radars, we analyze two different datasets by means of maximum likelihood (ML) parameter estimation as well as the root mean square error (RMSE) performance. We not only investigate log-logistic model, but also compare it with other popular clutter models, namely, log-normal, Weibull, and Nakagami. It shows that the log-logistic model achieves the smallest standard deviation (STD) error in parameter estimation, as well as the best goodness-of-fit and smallest RMSE for both poor and good foliage clutter signals.http://dx.doi.org/10.1155/2010/873070 |
spellingShingle | Sherwood W. Samn Jing Liang Qilian Liang A Propagation Environment Modeling in Foliage EURASIP Journal on Wireless Communications and Networking |
title | A Propagation Environment Modeling in Foliage |
title_full | A Propagation Environment Modeling in Foliage |
title_fullStr | A Propagation Environment Modeling in Foliage |
title_full_unstemmed | A Propagation Environment Modeling in Foliage |
title_short | A Propagation Environment Modeling in Foliage |
title_sort | propagation environment modeling in foliage |
url | http://dx.doi.org/10.1155/2010/873070 |
work_keys_str_mv | AT sherwoodwsamn apropagationenvironmentmodelinginfoliage AT jingliang apropagationenvironmentmodelinginfoliage AT qilianliang apropagationenvironmentmodelinginfoliage AT sherwoodwsamn propagationenvironmentmodelinginfoliage AT jingliang propagationenvironmentmodelinginfoliage AT qilianliang propagationenvironmentmodelinginfoliage |