The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Un algorithme qui détecte la position du pic d'écho de surface dans un profil de plage d'écho radar a été développé pour le radar de précipitation (PR) TRMM. Le but de la détection des pics d'écho de surface est de déterminer la fenêtre de plage dans laquelle les données de « suréchantillonnage » sont collectées. La position de l'écho de surface dans le profil de distance est variable en raison du changement systématique de l'altitude géodésique du satellite et de la topographie de la surface. Le contrôle dynamique de la fenêtre de plage de suréchantillonnage à l'aide de l'algorithme de détection de surface contribue de manière significative à la réduction du débit de données PR qui devrait être envoyé à la station au sol. L'algorithme utilise un filtre de suivi α-β et a trois fonctions : suivi de surface, détection de verrouillage et initialisation de la boucle de suivi. Après le lancement du satellite TRMM, une série de vérifications initiales du PR a été réalisée. Les performances de l'algorithme ont été évaluées lors du contrôle initial et du fonctionnement du PR pendant deux ans. Les résultats indiquent que l’algorithme fonctionne comme prévu et répond fondamentalement aux spécifications ; cependant, il s'avère que certaines fonctions telles que l'algorithme d'initialisation de la boucle de suivi doivent être améliorées.
Toshiaki KOZU
Shinsuke SATOH
Hiroshi HANADO
Takeshi MANABE
Minoru OKUMURA
Ken'ichi OKAMOTO
Toneo KAWANISHI
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Toshiaki KOZU, Shinsuke SATOH, Hiroshi HANADO, Takeshi MANABE, Minoru OKUMURA, Ken'ichi OKAMOTO, Toneo KAWANISHI, "Onboard Surface Detection Algorithm for TRMM Precipitation Radar" in IEICE TRANSACTIONS on Communications,
vol. E83-B, no. 9, pp. 2021-2031, September 2000, doi: .
Abstract: An algorithm that detects the surface echo peak position in a radar echo range profile has been developed for the TRMM Precipitation Radar (PR). The purpose of the surface echo peak detection is to determine the range window in which "over-sample" data are collected. The surface echo position in the range profile is variable due to the systematic change of satellite geodetic altitude and surface topography. The dynamic control of the over-sample range window using the surface detection algorithm contributes significantly to the reduction of PR data rate that should be sent to the ground station. The algorithm employs an α-β tracking filter and has three functions; surface tracking, lock-off detection and tracking loop initialization. After the launch of the TRMM satellite, a series of initial check-out of the PR was conducted. The performance of the algorithm was evaluated through the initial check-out and two-years operation of the PR. The results indicate that the algorithm is working as expected and basically meets the specification; however, it is found that some functions such as the tracking loop initialization algorithm need to be improved.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e83-b_9_2021/_p
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@ARTICLE{e83-b_9_2021,
author={Toshiaki KOZU, Shinsuke SATOH, Hiroshi HANADO, Takeshi MANABE, Minoru OKUMURA, Ken'ichi OKAMOTO, Toneo KAWANISHI, },
journal={IEICE TRANSACTIONS on Communications},
title={Onboard Surface Detection Algorithm for TRMM Precipitation Radar},
year={2000},
volume={E83-B},
number={9},
pages={2021-2031},
abstract={An algorithm that detects the surface echo peak position in a radar echo range profile has been developed for the TRMM Precipitation Radar (PR). The purpose of the surface echo peak detection is to determine the range window in which "over-sample" data are collected. The surface echo position in the range profile is variable due to the systematic change of satellite geodetic altitude and surface topography. The dynamic control of the over-sample range window using the surface detection algorithm contributes significantly to the reduction of PR data rate that should be sent to the ground station. The algorithm employs an α-β tracking filter and has three functions; surface tracking, lock-off detection and tracking loop initialization. After the launch of the TRMM satellite, a series of initial check-out of the PR was conducted. The performance of the algorithm was evaluated through the initial check-out and two-years operation of the PR. The results indicate that the algorithm is working as expected and basically meets the specification; however, it is found that some functions such as the tracking loop initialization algorithm need to be improved.},
keywords={},
doi={},
ISSN={},
month={September},}
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TY - JOUR
TI - Onboard Surface Detection Algorithm for TRMM Precipitation Radar
T2 - IEICE TRANSACTIONS on Communications
SP - 2021
EP - 2031
AU - Toshiaki KOZU
AU - Shinsuke SATOH
AU - Hiroshi HANADO
AU - Takeshi MANABE
AU - Minoru OKUMURA
AU - Ken'ichi OKAMOTO
AU - Toneo KAWANISHI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E83-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2000
AB - An algorithm that detects the surface echo peak position in a radar echo range profile has been developed for the TRMM Precipitation Radar (PR). The purpose of the surface echo peak detection is to determine the range window in which "over-sample" data are collected. The surface echo position in the range profile is variable due to the systematic change of satellite geodetic altitude and surface topography. The dynamic control of the over-sample range window using the surface detection algorithm contributes significantly to the reduction of PR data rate that should be sent to the ground station. The algorithm employs an α-β tracking filter and has three functions; surface tracking, lock-off detection and tracking loop initialization. After the launch of the TRMM satellite, a series of initial check-out of the PR was conducted. The performance of the algorithm was evaluated through the initial check-out and two-years operation of the PR. The results indicate that the algorithm is working as expected and basically meets the specification; however, it is found that some functions such as the tracking loop initialization algorithm need to be improved.
ER -