November 2018
Intermediate to advanced
272 pages
6h 51m
Japanese
book
エレガントなSciPy ―Pythonによる科学技術計算
by Juan Nunez-Iglesias, Stéfan van der Walt, Harriet Dashnow, 山崎 邦子, 山崎 康宏
Content preview from エレガントなSciPy ―Pythonによる科学技術計算
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101
4.7 実世界の応用例：レーダデータの解析
4.7
実世界の応用例：レーダデータの解析
線形変調した
FMCW
（
FM
連続波、
Frequency-Modulated Continuous-Wave
）レーダは、信号
処理に
FFT
アルゴリズムを広く利用しており、
FFT
の様々な応用例を提供してくれます。本節で
は
FMCW
レーダから得られた実際のデータを使い、代表的な応用の
1
つである目標検知を紹介し
ます。
おおまかに言うと、
FMCW
レーダは以下のように機能します（詳しくは次ページの囲み「簡単
な
FMCW
レーダシステム」と図
4-19
を参照）。
1.
まず、周波数が変動する信号が生成されます。この信号がアンテナから送信され、レーダか
ら離れる方向に外向きに伝搬します。信号が対象物にぶつかると、信号の一部が反射されて
レーダに戻り受信され、送信された信号の複製と掛け合わせられたのち、サンプリングさ
れ、数値として配列に格納されます。レーダ信号の解析の目的は、この数値を解釈して意味
のある結果を得ることです。
2.
信号の掛け合わせのステップは重要です。学校で勉強した三角関数の公式を思い出してくだ
さい。
sin(xt) sin(yt) =
1
2
sin (x − y)t +
π
2
− sin (x + y)t +
π
2
3.
公式により、受信した信号を送信した信号と掛け合わせると、送信した信号と受信した信号
の周波数の差と和の
2
つの周波数成分がスペクトルに現れることが予期されます。
4.
差の成分は、信号が反射されてからレーダに戻るまでの時間（つまり、対象物と我々との距 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.