Low-Cost Radar Techniques for Congested Environments

Abstract

The radio frequency spectrum is overcrowded by the ever-increasing number of technologies that use it. Functioning within the spectrum can be and often is a difficult task that leads to complications due to the congestion from different users and technologies operating at the same desired frequencies. In particular, this thesis will explore two types of interference, a common and dangerous side effect of the congested RF spectrum, that occur between radar and communications systems: wideband interference and out-of-band interference. Wideband technologies operate across a broad range of frequencies that can overlap and encompass narrow band systems, causing degradation in performance. This is commonly seen with wideband communication signals, such as 5G, interfering with narrowband radar systems. Further, these wideband signals are often sampled at different -- usually higher -- rates than the narrowband signals, making undersampling and its associated complications another undesirable consequence of wideband interference. Nevertheless, this work presents a novel post-processing algorithm that aims to recover lost information, resolving the issues caused by undersampling. In conjunction with this, a simulation of an (\Sigma-\Delta) analog-to-digital converter, developed in MATLAB, is used to simulate the sampling -- and thus the undersampling -- process that occurs when digitizing data. Adjacent frequency bands, such as the radar altimeter and 5G network bands, are likely to suffer from out-of-band interference. 5G networks reside in one of the most populous frequency bands, ranging from 3.7 to 4.2 GHz. Radar altimeters are allocated directly above this, in the adjacent band from 4.2 to 4.4 GHz. Radar altimeters are used in aircraft for landing, low-visibility flights, and other flight maneuvers. 5G emissions can cause out-of-band interference on radar altimeters, causing performance loss in the radar altimeter's receiver. It is often due to the low quality front-end filters that cannot filter out lower band emissions that this interference occurs, however, it is also possible for spurious 5G emissions to leak into the radar altimeter band. This work aims to understand out-of-band interference and how different post-processing techniques -- namely, matched filtering and stretch processing -- are able to mitigate this interference. Furthermore, this includes experimentation and analysis to understand radar altimeters and 5G networks both individually and in combination. This thesis introduces three main contributions: an algorithm to recover undersampled information, an analog-to-digital converter simulation, and an analysis of 5G and radar altimeter signals and their interactions. Ultimately, this thesis simulates, experiments, and analyzes congestion in the RF spectrum with the intention of developing solutions that will contribute to mitigating the negative effects caused by coexistence.