A fork of LD-Decode, the decoding software powering the Domesday86 Project. This version has been modified to work with the differences found in the tracked RF drum head signals taken directly from videotapes.
I am a young systems engineer in Paris, recently graduated in embedded systems. Electronics and code being my passions, I enjoy working on innovative open-source/hardware projects.
Dual language site - english and french.
Using an RTL-SDR device to do spectrum analysis. Uses numpy, pyQtGraph, rtlsdr modules. Short, sweet, and to the point.
This textbook acts as a hands-on introduction to the areas of DSP, SDR, and wireless communications. It is designed for someone who is:
An example is a Computer Science student interested in a job involving wireless communications after graduation, although it can be used by anyone itching to learn about SDR who has programming experience. As such, it covers the necessary theory to understand DSP techniques without the intense math that is usually included in DSP courses. Instead of burying ourselves in equations, an abundance of images and animations are used to help convey the concepts, such as the Fourier series complex plane animation below. I believe that equations are best understood after learning the concepts through visuals and practical exercises. The heavy use of animations is why PySDR will never have a hardcopy version being sold on Amazon.
rtl_power_fftw is a program that obtains a power spectrum from RTL devices using the FFTW library to do FFT.
It is inspired by the program rtl_power in librtlsdr. However, the said program has several deficiencies that limit its usage in demanding environments, such as radio astronomy. An inspection of rtl_power in hope of modifying it and obtaining better performance resulted in the conclusion that it would be an infeasible task. Measurements of FFT performance showed that the leading library in the field of FFT - fftw - makes mincemeat of the routine used in rtl_power, even on simple processors such as raspberryPi.