Signal identification in congested RF spectrum

近年来，智能无线电在各种军事和商业应用中的使用需求不断增加，例如无线电监视和干扰。为了有效的干扰，而不是使用类似噪声的信号，应该使用与目标相同类型的信号。如果干扰机具有检测空中现有信号的存在并识别目标信号的类型的能力，使得其相应地适配所生成的干扰信号，则这将是可能的。此外，拥塞的宽带RF频谱可以包含来自多个蜂窝网络的信号，并且对于干扰机来说，能够识别标准蜂窝信号以便击败任何蜂窝网络威胁变得重要。为此，该项目的目的是有助于开发算法，用于在拥挤的宽带RF频谱中感知和识别现有的蜂窝标准信号。设计的解决方案将通过使用真实的捕获数据进行验证，这些数据将由行业合作伙伴艾伦先锋提供。开发的算法将被纳入艾伦先锋的软件定义无线电平台，以扩展其功能，超越其目前的干扰功能。通过将这些算法纳入其平台，这家总部位于哥伦比亚的高科技公司可以增加其对市场的影响力。

In recent years, there has been an increasing demand for the usage of intelligent radios with various military and commercial applications, such as radio surveillance and jamming. For an efficient jamming, instead of using a noise-like signal, the same type of signal as the target one should be used. This would be possible if the jammer has the capability to detect the presence of existing signals in the air and identify the type of the target signals, such that it adapts the generated jamming signals accordingly. Furthermore, the congested wideband RF spectrum can contain signals from multiple cellular networks, and it becomes important for the jammer to be able to identify standard cellular signals in order to defeat any cellular network threats. To this end, the proposed project aims to contribute to developing algorithms for sensing and identification of existing cellular standard signals in congested wideband RF spectrum. The devised solutions will be verified by using real captured data, which will be provided by the industry partner, Allen Vanguard.The developed algorithms will be incorporated in the Allen Vanguard's software-definedradio platforms to extend their capabilities beyond their current jamming functionalities. By incorporating such algorithms within its platforms, this Canadian-based high-tech company can increase its influence on the market.