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.

figs/TI_connection.jpg

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).