Difference between revisions of "Experiments with RTL SDR"

From Pabut
Jump to navigation Jump to search
(Created page with "Got an RTL-SDR stick and downconverter. What to use it to build RF HEATMAPS, specifically to monitor a new Solar Installation going in at a local school. Plan is to create a h...")
 
Line 2: Line 2:
  
 
System contains:
 
System contains:
NooElec NESDR Mini2 - RTLSDR USB  
+
*NooElec NESDR Mini2 - RTLSDR USB  
NooElec Ham it Up - 125Mhz Uconverter
+
*NooElec Ham it Up - 125Mhz Uconverter
Debian Wheezy Linux
+
*Debian Wheezy Linux
RTL-SDR http://sdr.osmocom.org/trac/wiki/rtl-sdr
+
*RTL-SDR http://sdr.osmocom.org/trac/wiki/rtl-sdr
 +
*heatmap https://github.com/keenerd/rtl-sdr-misc
  
 
First run rtl_power to scan a band:
 
First run rtl_power to scan a band:
 
 
 
 
  timeout 1h rtl_power -f139M:139.35M:100 -p59 ~/20M_band.csv
 
  timeout 1h rtl_power -f139M:139.35M:100 -p59 ~/20M_band.csv
  
Line 19: Line 17:
 
  "-p59" compensate 59 parts-per-million error in the tuner
 
  "-p59" compensate 59 parts-per-million error in the tuner
 
  "~/20M_band.csv" where to save the data
 
  "~/20M_band.csv" where to save the data
 +
 +
Then when that's done, feed it into the heatmap program:
 +
 +
python heatmap.py ~/20M_band.csv ~/20M_band.png
 +
 +
Where:
 +
"python heatmap.py" is the python program to parse the data
 +
"~/20M_band.csv" input data
 +
"~/20M_band.png" output image
 +
 +
 +
"

Revision as of 10:55, 30 August 2015

Got an RTL-SDR stick and downconverter. What to use it to build RF HEATMAPS, specifically to monitor a new Solar Installation going in at a local school. Plan is to create a heatmap before the system goes online and then after to see if any new interference is detected.

System contains:

First run rtl_power to scan a band:

timeout 1h rtl_power -f139M:139.35M:100 -p59 ~/20M_band.csv

Where:

"timeout 1h" is a GNU coreutils program that will send an ineterupt to the program after 1 hour
"rtl_power" the binary program
"-f139M:139.35M:500" scan the band from 139.00MHz to 139.35MHz in 500 Hz steps (actually 14.00 to 14.350 through the upconverter)
"-p59" compensate 59 parts-per-million error in the tuner
"~/20M_band.csv" where to save the data

Then when that's done, feed it into the heatmap program:

python heatmap.py ~/20M_band.csv ~/20M_band.png

Where:

"python heatmap.py" is the python program to parse the data
"~/20M_band.csv" input data
"~/20M_band.png" output image


"