Geniux Warrior 24.02
New release of the Geniux Warrior manifest. It contains a list of Git repositories and their respective commit hashes that allow building images and SDKs defined by the meta-gnss-sdr OpenEmbedded layer
The name Geniux comes from GNSS-SDR for Embedded GNU/Linux.
Geniux Warrior v24.02 is a customized embedded Linux distribution based on the Yocto Project version 2.7.4. Main features:
- Development tools: Automake v1.16.1, CMake v3.14.1, GCC v8.3.0 (+ libgfortran), make v4.2.1, ninja v1.9.0, Python v2.7.18 and v3.7.7.
- Goodies for signal processing:
- SDR framework: GNU Radio v3.8.2.0.
- Number crunching libraries: Armadillo v10.8.0, FFTW v3.3.9, Lapack v3.7.0, VOLK v2.3.0.
- C++ supporting libraries: Boost v1.69.0, gflags v2.2.2, glog v0.5.0, googletest v1.11.0, Matio v1.5.23, Protocol Buffers v3.6.1, Pugixml v1.11.4.
- Graphical representation: gnss-sdr-monitor v1.0, Gnuplot v5.2.2.
- Software drivers and tools for RF front-ends: UHD v3.15.LTS (+ gr-uhd), gr-osmosdr v0.2.3 (+ rtl-sdr and hackrf), gr-iio v0.3, libiio v0.23, libad9361-iio v0.2, iio-oscilloscope v0.14.
- GNSS-SDR v0.0.19.
More info at https://gnss-sdr.org/docs/tutorials/cross-compiling/
Changes with respect to Geniux Warrior 23.04
- Updated
meta-gnss-sdr
layer. - Updated developer scripts.
- libhackrf: update to new repository github.com/greatscottgadgets/hackrf
- libiio: repo branch changed from master to main.
- Removed unused
ezdma
driver. - Updated GNSS-SDR to v0.0.19.
How to build images and the SDK
With Docker already installed on your system, build the SDK and images for your preferred machine:
$ git clone https://github.com/carlesfernandez/yocto-geniux
$ cd yocto-geniux
$ ./geniux-builder.sh warrior 24.02 zedboard-zynq7
The generated yocto-geniux image also provides an interactive mode that allows users to make changes, experiment, fine-tune, and generate their own custom images and SDKs according to their specific requirements in a virtualized environment. Please check the README.md file of that repository for instructions.
Copyright and Licence
Copyright: © 2016-2024 Carles Fernández-Prades, CTTC. All rights reserved.
The content of this repository is released under the MIT licence.
Acknowledgements
This work was partially supported by Grant PID2021-128373OB-I00 funded by MCIN/AEI/10.13039/501100011033.