Texas Instruments radarsΒΆ
Since we used these radars for data capturing and analysis, we need to give necessary information on how to use these radars with PyRAPID.
There are many versions of the inegrated radars by TI, which are supporing different features.
Some of them, like AWR1443
and AWR1642
, have on-chip processors enabling users to implement
an embedded radar system. However, it is not useful for the system development stage since
it requires to determine the memory allocation strategies and know DSP architectures, which
take time to understand them. And if one knows them, it is only useful for working with TI radars
and it is a headache to move to another radar. Nevertheless, there are many demos available
by TI either developed fully on the chip or partially on the chip and PC
(see here).
In contrast, PyRAPID provides a fast and efficient algorithm implementation just using Python. The following figure shows connections for capture raw radar data from Gigabit Ethernet. See examples in Code Examples for PyRAPID for dumping raw radar data into a binary file.

The user application determines FMCW configuration parameters. Important parameters are (see definitions in Chirp programming):
Frequency slope
chirp ramp end time
idle time
Sampling rate
Number of ADC samples in a chirp
ADC start time
Frame period
Number of chirps in a frame per Tx channel
Define Profile, Chirp, and Frame configurations for the application using classes in Defining TI FMCW parameters in order to get valid values of range/Doppler or velocity/angle for that configuration.
Note
Currently, in order to capture the data directly from Ethernet, you must run and
configure the radar via mmwave studio
software, and before connecting to DCA1000
board, PyRAPID should connect
to the ethernet. Then, you can trigger the frame (see Code Examples for PyRAPID).