Fromage, Jacob;
Masson, Rikki;
Beasley, Piers J;
Ritchie, Matthew A;
Chetty, Kevin;
(2024)
Quantifying Performance Benefit of Adaptive Active-Passive Mode-Switching Using Experimental Data.
In:
Proceedings of the 2024 International Radar Symposium (IRS).
IEEE: Wroclaw, Poland.
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Abstract
In this paper we investigate the potential benefits of implementing an adaptive active-passive mode-switching algorithm to a multi-function radio frequency (RF) system for sensing. This research was performed using experimental radar data captured during a trial of a hybrid active-passive capable software defined radio (SDR) based radar. An outline of the system used during the experiment is included within the paper, as well as an overview of the experiment itself. Details of the post-processing performed on the data and results produced from running the algorithm on the experimental data are shown. The performance benefits of a real-time application of the algorithm are quantified and verified in the form of figures and tables. In some cases a 60% reduction in active transmission time is realised, as well as a 20% increase in mean SNR over time when compared with data not implementing the algorithm. The strengths and limitations of the algorithm in its current form are discussed as well as directions for future work.
| Type: | Proceedings paper |
|---|---|
| Title: | Quantifying Performance Benefit of Adaptive Active-Passive Mode-Switching Using Experimental Data |
| Event: | 2024 International Radar Symposium (IRS) |
| Location: | Wroclaw, Poland |
| Dates: | 1 Jul 2024 - 4 Apr 2024 |
| ISBN-13: | 978-83-956020-9-2 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://ieeexplore.ieee.org/document/10644249 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Hybrid Radar, Multifunction, Multi-function, Passive Radar, Sensor Fusion, Adaptive Signal Processing, Software Defined Radio, Experimental data |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10191463 |
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