Neuromorphic RF sensing and processing

该项目的目的是从硬件和软件两个层面研究射频传感中的神经形态解决方案。该项目的主要目标是：-熟悉雷达原理和射频传感系统的基本概念。-熟悉人工智能和最大似然技术领域的基本概念，对传感系统特别感兴趣。-确定SNN在处理射频数据时的限制和培训要求；-识别和设计大脑启发的无源射频传感模式，以产生尖峰输出；-基于模拟和真实数据，为射频系统设计和开发新的NM/SNN框架。-根据莱昂纳多提供的、在SSP和S实验室获得的真实数据，验证开发的框架。-制定测试战略，评估和演示开发的新型NM/SNN模型和技术的性能，并将性能与传统处理方法进行比较。-调查所开发解决方案的神经形态硬件实验；-在世界领先的期刊和会议上传播这项研究的成果。

The aim of this project will be to investigate neuromorphic solutions in RF sensing at both hardware and software level. The main objectives of the project will be:- To become familiar with fundamental concepts of radar principles and RF sensing systems.- To become familiar with fundamental concepts in the field of AI and ML, with a particular interest in sensing systems.- To identify constraints and training requirements for SNNs when dealing with RF data;- To identify and design brain inspired passive RF sensing modes to generate spiking outputs;- To design and develop novel NM/SNN frameworks, for RF systems, based on simulated and real data.- To validate the developed framework on real data provided by Leonardo and acquired at the SSP&S labs.- To devise a testing strategy to evaluate and demonstrate the performance of the novel NM/SNN models and techniques developed, and compare performance with traditional processing methods.- To investigate the experimentation with Neuromorphic hardware of the developed solutions;- To disseminate outcomes from this research, in world leading journals and conferences.