TomRoelandts.com

Frequency response plots are often shown with normalized frequency on the X-axis. This sometimes confuses people. The normalized frequency is computed by dividing the true frequency by the sampling rate. Hence, the sampling rate itself has… read more

Before you can digitally process an analog (i.e., real-world) signal, you have to convert it to a digital form by sampling it. A very important aspect of this conversion is that you should avoid clipping the original signal. Clipping happens when… read more

How do you plot meteor power profiles from BRAMS data? The straightforward approach fails, but some simple filtering is enough to bring out the true profile… read more

This article is a wrap-up of what happened on TomRoelandts.com in 2014. read more

After mentioning Rosetta in June, there is another deep space mission that I want to bring to your attention. The final preparations for the flyby of Pluto by the New Horizons spacecraft have started. New Horizons will be… read more

After explaining how amplitude modulation works, the next step is Frequency Modulation (FM), which you might be more familiar with, since it is widely used for radio broadcasting. In practice, a carrier for FM broadcast radio would have… read more

Using modulation in radio communications is unavoidable. The simplest modulation technique is Amplitude Modulation (AM), where the amplitude of a carrier is varied according to the message that is to be transmitted. A carrier is… read more

This article is on a new method for detecting meteor reflections in radio signals for the BRAMS network. As shown below, these reflections are typically viewed as spectrograms. Hence, a straightforward way to approach the detection problem is to… read more

The famous “Wow!” signal is a radio signal that was received on 15 August 1977 as part of the SETI program. After all these years, it is still the most tantalizing candidate for being a true interstellar signal. Its name comes from the manually written word “Wow!” on… read more

This is the second of a two-part article on the PDART algorithm. It explains most of the nitty-gritty details. The PDART algorithm needs two extra input parameters to do its magic, a threshold and a gray level. After each SIRT iteration, each pixel of… read more