VEGA
Data Repository of Passive Radar Measurements

Data sets listed in the VEGA repository can be used only for research purposes.

Any commercial use of these data sets is forbidden.
 

This database is open, contributions to the repository are welcome.

Click on the Title of the data set to open the detailed description of the measurement !

Meta data fields:
 

• Meta data version: 1.2.0

• VEGA data set ID: <Measurement ID in the VEGA database>

• Illuminator of Opportunity : Type of the used illuminator. e.g. FM/DVB-T/DAB ..

• Measurement frequency: Operating frequency of the IOP and the radar

• Measurement date: Has of format of ddmmyyyy

• Configuration ID: Identifies the used measurement arrangement or radar configuration

• Surveillance ID: Identifies the data record set in the current configuration.

• Measurement site: Name of the measurement location

• Rx latitude: Radar lat. coordinate

• Rx longitude: Radar long. coordinate.

• Tx latitude: List of latitude coordinates of the used illuminators

• Tx longitude: List of longitude coordinates of the used illuminators

• Radar azimuth bearing: Main direction of the surveillance antenna or antenna array

• Rx Hardware: Name of the receiver hardware used for the measurement

• Rx unit ID: Hardware unit index

• Radar System versions: PCB and SW versions of the radar unit

• Reference channel antenna(s): Antenna structure used for the reference channel

• Surveillance channel antenna(s): Antenna structure used for the surveillance channel

• Reference channel indices: Designate antenna channels. Counted from 0.

• Surveillance channel indices: Designate antenna channels. Counted from 0.

• Data type: Data can be raw or decimated IQ samples

• Sampling frequency: signal sample rate

• CPI length: Time interval of a recorded signal block

• Number of records: Number of coherent blocks that van be found in a surveillance

• Data size: Total size in MB

• Additional comments:

Example Python code to convert IQ data to MATLAB:

import numpy as np
import scipy.io as io

​

fname_prefix = "VEGAM20180313HR2U0C0S0FM_"
start_index = 240
stop_index = 240
for i in np.arange(start_index,stop_index+1,1):
    print("Converting: ",(fname_prefix+str(i)+".npy"))    
    x = np.load(fname_prefix+str(i)+".npy") # Load numpy array
    io.savemat((fname_prefix+str(i)+".mat"),dict(x=x)) # Save to matlab file

Referencing:

You can cite the used data set in the following format:

Tamas Pető (2019), Vega: Data Repository of Passive Radar Measurements, <DATA SET ID>, [Data set]. http://tamaspeto.com/vega