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Low, High, and Band pass filter

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TTA
TTA am 23 Sep. 2019
Kommentiert: TTA am 27 Sep. 2019
Hi,
Please Help me solve a worrying problem. I want to use low pass, high pass and bandpass filter for the Temperature profile of the attached file. I want to use 10km for the lowpass, 1km for the high pass and 1-10km for the bandpass filters. Any filtering method would do
thanks
  9 Kommentare
TTA
TTA am 27 Sep. 2019
Yes the altitude is not regular in space so we have to interpolate it to have a regular 0.02 (20m) space and in the end it stops at 60km. Since this is not in time, we can assume that every meter (m) to the time (sec). The lowpass filter will have a cut off of higher time (or m) which means a lower frequency.
TTA
TTA am 27 Sep. 2019
Bearbeitet: TTA am 27 Sep. 2019
Or may be I didn't get the understanding. This is why I need help

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Shubham Gupta
Shubham Gupta am 27 Sep. 2019
Assuming you can interpolate the data and make altitude to vary at fixed step of 0.02 km and 1km equivalent to 1sec.
To make butterworth filter you can use:
Sampling_Space = 0.02; % km, equivalent to 50 Hz
Low_filt = 10; % km, equivalent to 0.1 Hz
High_filt = 1; % km, equivalent to 1 Hz
Band_filt = [10 1]; % km, equivalent to 0.1Hz to 1Hz
[bl,al] = butter(2,(2*Sampling_Space)/Low_filt,'low');
[bh, ah] = butter(2,(2*Sampling_Space)/High_filt,'high');
[bb, ab] = butter(2,(2*Sampling_Space)/Band_filt,'bandpass');
Now to filter your data :
temperature_low_filtered = filter(bl,al,temperature);
temperature_high_filtered = filter(bh,ah,temperature);
temperature_band_filtered = filter(bb,ab,temperature);
I hope it helps !

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