Study of adaptive frequency notched radar waveform

Adaptive frequency notched radar waveform is examined in this report. The signal sent out by radar will encounter interference and noise when transmitting through the air. Then, when the interfered signals are transmitting back, the matched filter outcome will not be good because of the interference...

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Main Author: Guo, Yitong
Other Authors: Lu Yilong
Format: Final Year Project
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/60349
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-603492023-07-07T16:15:09Z Study of adaptive frequency notched radar waveform Guo, Yitong Lu Yilong School of Electrical and Electronic Engineering DRNTU::Engineering Adaptive frequency notched radar waveform is examined in this report. The signal sent out by radar will encounter interference and noise when transmitting through the air. Then, when the interfered signals are transmitting back, the matched filter outcome will not be good because of the interference. If we know which range of frequency will be interfered, we could remove that frequency from the whole band before sending out the signal. Thus, the matched filter outcome will be improved a lot. The two different kinds of frequency notched radar waveform are examined in this report. Ultra-low sidelobe waveform is another way to improve the matched filter outcome and lower down the sidelobe level. By changing the time versus frequency waveform from the simple linearity, we expect the performance of matched filter output will be improved. To achieve this, we added two tails with different slope to the original linear graph. Besides, LFM windowing can also reduce the sidelobe level. It simply adds a window function between the matched filter impulse response and received signal. PSO (Particle Swarm Optimization), as the stochastic evolutionary computation optimization technique is also introduced in this report. Deriving from the ultra-low sidelobe waveform, we aim to make it a generalization and find an optimization. By using the PSO method, we expect to come out a best design of time versus frequency waveform in order to achieve a low sidelobe. Also, we use PSO to optimize the notched frequency radar waveform. In this report, the software part of adaptive notched radar waveform is studied. By using the software Matlab, we simulate the performance and matched filter output of radar waveform. Bachelor of Engineering 2014-05-26T09:10:17Z 2014-05-26T09:10:17Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60349 en Nanyang Technological University 72 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Guo, Yitong
Study of adaptive frequency notched radar waveform
description Adaptive frequency notched radar waveform is examined in this report. The signal sent out by radar will encounter interference and noise when transmitting through the air. Then, when the interfered signals are transmitting back, the matched filter outcome will not be good because of the interference. If we know which range of frequency will be interfered, we could remove that frequency from the whole band before sending out the signal. Thus, the matched filter outcome will be improved a lot. The two different kinds of frequency notched radar waveform are examined in this report. Ultra-low sidelobe waveform is another way to improve the matched filter outcome and lower down the sidelobe level. By changing the time versus frequency waveform from the simple linearity, we expect the performance of matched filter output will be improved. To achieve this, we added two tails with different slope to the original linear graph. Besides, LFM windowing can also reduce the sidelobe level. It simply adds a window function between the matched filter impulse response and received signal. PSO (Particle Swarm Optimization), as the stochastic evolutionary computation optimization technique is also introduced in this report. Deriving from the ultra-low sidelobe waveform, we aim to make it a generalization and find an optimization. By using the PSO method, we expect to come out a best design of time versus frequency waveform in order to achieve a low sidelobe. Also, we use PSO to optimize the notched frequency radar waveform. In this report, the software part of adaptive notched radar waveform is studied. By using the software Matlab, we simulate the performance and matched filter output of radar waveform.
author2 Lu Yilong
author_facet Lu Yilong
Guo, Yitong
format Final Year Project
author Guo, Yitong
author_sort Guo, Yitong
title Study of adaptive frequency notched radar waveform
title_short Study of adaptive frequency notched radar waveform
title_full Study of adaptive frequency notched radar waveform
title_fullStr Study of adaptive frequency notched radar waveform
title_full_unstemmed Study of adaptive frequency notched radar waveform
title_sort study of adaptive frequency notched radar waveform
publishDate 2014
url http://hdl.handle.net/10356/60349
_version_ 1772825950811062272