kaklik

Hello everyone,

I now came across this thread while researching for my dissertation and felt compelled to chime in, as I find this idea of a software-defined lightning detector very promising.

Introduction

The concept of upgrading the current lightning detection systems to align with today's technology levels is both timely and required. Compared to the limitations of existing systems like Blitzortung (or many other commercial networks), the innovation potential with the use of SDR is immense.

The current approach taken by most lightning networks focuses on processing individual impulses. However, I believe the future lies in processing signal fragments. The minimum length of these signal fragments should be 500ms or more, with a bandwidth of at least a few hundred kHz. This approach offers a more physically and scientifically relevant description of lightning. I tried to explain that necessarily in my article: https://amt.copernicus.org/articles/16/547/2023/

Implementation

From my perspective, the challenge of localizing lightning strikes is not very hard. I've prepared a relatively simple notebook that demonstrates how to localize lightning strikes from signal fragments: https://github.com/ODZ-UJF-AV-CR/CRREAT_cars/blob/master/VLF_lightning/VLF_location.ipynb The real challenge lies in how to present the results in a relevant manner on the map and to implement a scalable solution.

Given today's computational power, it's sensible to design the calculations for GPU processing, as this problem is highly parallelizable. With up to 1,000,000 signals per day, data compression becomes crucial to reduce data flow and improve response times, as the bottleneck is likely to be data transfer speed, not computational power in the case of worldwide deployment.

Conclusion

Based on my research from a few past years, I fully support this idea of a software-defined lightning detector. The focus should be on processing signal fragments with an appropriate length corresponding to lightning duration and bandwidth and leveraging GPU processing for scalability.

The next step is to check the possibility of extracting the signal fragments from KiwiSDR receiver stations. The fragments need to be generated at the station side from the circle buffer, based on a trigger (e.g. energy of signal - pulse width and length). That is needed because the required signal fragment bandwidth is very likely to be wider than the usual data transfer speed from the receiver.