LRF – Radio Frequency Laboratory

The MSc. candidate Rafael Licursi successfully defended his thesis, in which he proposed novel Techniques To Locate And Identify Radars With Low Volume, Weight, Costs And Processing Capabilities.

This research proposes signal processing techniques that look at  radiofrequency peculiarities in order to soften the processing workload and to allow the design of radar detectors that present low volume, weight, costs and available computational power. Experiments were carried out with a prototype of an Electronic Support Measures (ESM)  system with tablet processing, based on Software–Defined Radio (SDR). Results show that the performance of the proposed pulse measurement  technique degrades significantly only when the pulse amplitudes are  ≤ 3.7 mV at the input of the used SDR. They also show that the suggested direction–finding method presents Gaussian distributions for the measurements, with a standard deviation as high as the lower the amplitude of incoming pulses, which allows, according to the latter, to make inferences about the former. Benefiting from this, the developed pulse–clustering algorithm defined, in front of 6 distributions, clusters of pulses with enclosure rates ≥ 92.71 %. Finally, the results show that the proposed pattern recognition algorithm, when it received a cluster of pulses with patterns of 4 simulated radars, with different types of antenna scan, deinterleaved the 4 patterns, with rates of correct assignment of the pulse repetition interval ≥ 96.30%, besides estimating the pulse repetition interval with errors of the order of 10^-5. This study is recommended for the areas of Radar Signal Processing, Direction  Finding, Pattern Recognition and Electronic Warfare.