# Radio Frequency Interference, Its Mitigation and Its Implications for the Civil Aviation Industry
## 4 Discussion and Future Work
### Current Research Challenges  
Another significant gap is the limited validation of theoretical models assessing interference-to-noise ratios. Many existing studies rely on simulations rather than real-world implementation, making it necessary to conduct field experiments in diverse geographical and environmental conditions to ensure accurate validation. Additionally, disparate regulatory standards across regions create inconsistencies in managing spectrum usage and interference control. A unified framework through international collaborations and shared data can help in establishing standardized mitigation practices, ensuring global aviation safety. The effectiveness of UAV-based RFI monitoring systems is also an area that needs further research. These systems have been proposed for interference detection, but their testing in varied terrains, such as urban, rural, and high-altitude environments, remains inadequate. Developing modular UAV platforms equipped with adaptive RF monitoring algorithms can optimize interference detection. Additionally, fragmented immunity and emission testing in integrated circuits (ICs) is a concern, as existing methods fail to evaluate immunity and emissions simultaneously. AI-driven predictive models and dual-channel analyzers could enhance these testing processes to ensure compliance with EMC standards. Another major challenge is the insufficient automation of VHF anomaly detection. It is also important to note that while many mitigation strategies emphasize front-door coupling--such as filtering and antenna shielding--back-door coupling presents more persistent challenges. These pathways often include unintentional entry points through power lines, cable harnesses, or structural seams. Effective protection requires comprehensive grounding, multi-layer shielding, and EMI-aware layout design, which are more complex to implement and validate. The literature still lacks field-tested frameworks specifically focused on this harder-to-control mechanism. While [PERSON] et al. [28] propose a multi-layer shielding model for UAVs, their simulations assume ideal ground reflection models and ignore Aircraft cabin resonance. In contrast, [PERSON] et al. demonstrate the real-world validation of interference thresholds but only for static scenarios. Our analysis suggests a hybrid validation approach that combines field testing with simulation to achieve scalable, reliable EMI certification. Future standards should mandate real-time in-flight data logging for evaluating signal integrity under operational loads. Traditional methods rely on manual monitoring, which can be inefficient and error-prone. Deploying machine learning models trained on historical data can help classify and predict anomalies in VHF aviation communications. Similarly, GNSS interference mitigation remains a challenge, as GNSS signals are highly vulnerable to jamming, spoofing, and out-of-band interference. Integrating inertial navigation systems (INS) and advanced signal processing algorithms can enhance resilience against such disruptions. Managing co-site interference in Aircraft communication systems is another ongoing issue. Existing transmitter and antenna designs are not optimized to minimize interference. Implementing electromagnetic simulations to refine antenna placement and spectrum usage, along with employing adaptive filtering systems, can help mitigate overlapping-frequency problems. Likewise, understanding near-field interactions in localizer antenna systems requires further research, as current studies do not sufficiently differentiate between near-field and far-field behaviors. Conducting real-world experiments alongside simulations would improve knowledge in this domain. Another gap exists in multi-band RF filtering, as current designs lack versatility. Advanced materials such as Polytetrafluoroethylene (PTFE) could improve filter efficiency. Testing these filters in both laboratory and operational settings will ensure their effectiveness.