The Research of Radar Adaptive Sampling Rate for Tracking Systems
碩士 === 大葉大學 === 電機工程研究所 === 89 === In order to solve target-maneuvering problems, an improved tracking algorithm has been developed in this thesis. In tracking system, if the sampling rate of system is too fast then the operation quantity of system will be bigger. However, if the sampling...
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ndltd-TW-089DYU004420132015-10-13T12:43:59Z http://ndltd.ncl.edu.tw/handle/84184208394517373800 The Research of Radar Adaptive Sampling Rate for Tracking Systems 雷達適應性掃描速率追蹤系統之研究 Chun-Chin Yu 余俊慶 碩士 大葉大學 電機工程研究所 89 In order to solve target-maneuvering problems, an improved tracking algorithm has been developed in this thesis. In tracking system, if the sampling rate of system is too fast then the operation quantity of system will be bigger. However, if the sampling rate of system is too slow then the tracking error will be bigger. So we want to create a tracking algorithm to reduce the operation quantity of system while keep a low tracking errors. The major frame of this thesis contains an Adaptive Sampling Rate Tracking Algorithm, adaptive extended Kalman filter and to utilize a data association technique denoted 1-step conditional maximum likelihood. Via this approach, target-maneuvering productive great errors can be decreased and the tracking system will obtain better performance. Moreover, in order to verify the approach of this thesis is really improved. We detail to analyze and to compare with three types of simulations of tracking algorithm and to hypothesis many different target track situations. We convince that the proposed approach will enhance the radar tracking performance and obtain better tracking results. Yi-Nung Chung 鍾翼能 2001 學位論文 ; thesis 75 zh-TW |
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碩士 === 大葉大學 === 電機工程研究所 === 89 === In order to solve target-maneuvering problems, an improved tracking algorithm has been developed in this thesis. In tracking system, if the sampling rate of system is too fast then the operation quantity of system will be bigger. However, if the sampling rate of system is too slow then the tracking error will be bigger. So we want to create a tracking algorithm to reduce the operation quantity of system while keep a low tracking errors. The major frame of this thesis contains an Adaptive Sampling Rate Tracking Algorithm, adaptive extended Kalman filter and to utilize a data association technique denoted 1-step conditional maximum likelihood. Via this approach, target-maneuvering productive great errors can be
decreased and the tracking system will obtain better performance.
Moreover, in order to verify the approach of this thesis is really improved. We detail to analyze and to compare with three types of simulations of tracking algorithm and to hypothesis many different target track situations. We convince that the proposed approach will enhance the radar tracking performance and obtain better tracking results.
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Yi-Nung Chung |
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Yi-Nung Chung Chun-Chin Yu 余俊慶 |
author |
Chun-Chin Yu 余俊慶 |
spellingShingle |
Chun-Chin Yu 余俊慶 The Research of Radar Adaptive Sampling Rate for Tracking Systems |
author_sort |
Chun-Chin Yu |
title |
The Research of Radar Adaptive Sampling Rate for Tracking Systems |
title_short |
The Research of Radar Adaptive Sampling Rate for Tracking Systems |
title_full |
The Research of Radar Adaptive Sampling Rate for Tracking Systems |
title_fullStr |
The Research of Radar Adaptive Sampling Rate for Tracking Systems |
title_full_unstemmed |
The Research of Radar Adaptive Sampling Rate for Tracking Systems |
title_sort |
research of radar adaptive sampling rate for tracking systems |
publishDate |
2001 |
url |
http://ndltd.ncl.edu.tw/handle/84184208394517373800 |
work_keys_str_mv |
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