Why handheld spectrum analyzers are inadequate for mission-critical services

As the world becomes increasingly digitized, advances in wireless innovations are driving demand for heightened RF spectrum monitoring. More wireless electronic devices mean more radio frequency interference (RFI) issues. And although RFI levels are usually small and intermittent, mission-critical communication applications can be seriously affected if the causes are not located and addressed rapidly. The nirvana is to identify and deal with RFI before they impact mission-critical applications. 

Hunting different interference sources has historically been conducted manually using handheld spectrum analyzers. These tools are still relevant in some circumstances: monitoring constant RFI sources, for example. However, with the ever-increasing number of RF-enabled devices, locating the causes of RFI using these tools is hit-and-miss, which is not accurate enough for mission-critical services dependent on high-fidelity data.  

What RFI sources can impact mission-critical services? 

RFI manifests itself in many formats and can be generated unintentionally or deliberately. RFI also exists naturally as thermal noise. Having the right tools to quickly detect, categorize, and locate unknown interference sources, or those transmitting on the wrong frequency range, is fundamental in a mission-critical situation. Although some forms of RFI can be random, these are the most common causes of RFI: 

• Illegally installed transmitters 
• Signal spoofing technology 
• Out-of-spec frequencies 
• Frequency clashes 
• Faulty/leaky equipment 
• Poor connections 
• Design issues 

Finding and detecting RFI often involves sending teams of engineers to different locations equipped with various portable spectrum analyzers and other RF monitoring equipment. However, apart from being time-consuming, battery-draining, labor-intensive, and impractical for remote installations, they pose serious concerns due to: 

1. Restricted RF performance: they will only be able to detect signals above specific parameters in frequency, power, noise, and timing conditions—potentially missing many RFI sources. 
2. Real time, operator driven interface: they have not been designed to identify and flag RF abnormalities automatically. With many RFO sources being transient, it simply takes too long to respond to the issue or there is a probability of intercept problem.    

RFI sources that can disrupt air traffic control systems or public safety communications, for example, tend to be erratic and short-lived. Causes can be anything from devices transmitting on the wrong frequency ranges to faulty radios in aircraft. Unless field engineers are in the right place at the right time, finding and classifying RFI using a handheld analyzer is extremely challenging. 

When monitoring the RF spectrum for mission services, all frequencies must be considered, and the deployed solution must provide wideband capabilities to ensure nothing is missed. The system should also facilitate real-time detection and identification of specific RFI events and timestamps, thus enabling informed decision-making based on risk levels.

Additionally, the solution must be agile, in line with RF monitoring requirements, and easily deployable as either a fixed network for long-term RF monitoring or a temporary solution that can quickly be deployed.    

Advantages of automated RF manual monitoring 

1. Operational  

By automating complex and time-consuming tasks, spectrum managers can efficiently collect and process actionable intelligence from a network of RF signal receivers, no matter how geographically diverse they are. They can also overcome the accuracy limitations associated with manual monitoring, including fatigue, a lack of training, human error, and the monotony of constantly watching for anomalies in a crowded spectrum.  

2. Accuracy  

Automated RF monitoring gives spectrum managers a real-time, geographically accurate, and actionable view of RF activity. With the help of detailed map overlays, it is possible to visualize and understand the RF status in a particular area and use interactive and intuitive interfaces to tailor spectrum monitoring to meet specific requirements. With this information, organizations can make swift and informed decisions to mitigate any adverse effects on their networks or within their area of responsibility—ensuring reliable and secure digital communication 24/7.  

3. Adaptability  

Automation improves the efficiency and accuracy of signal collection and analysis and also delivers the ability to scale, adapt, and centralize signal collection and analysis.   

Moreover, automation facilitates the fast deployment of a vast network of remote RF sensors and receivers, which collect and transmit data in real time, providing a comprehensive view of the spectrum environment. Such scalability empowers organizations to manage an increasing number of RF devices and networks and reduce the impact of interference on mission-critical services.    

Unknown environmental considerations  

In RF monitoring, the physical environment is critical but unpredictable. Weather can impact the operability of a fixed network of receivers or a standalone system and the fidelity of the data captured.   

During a mission-critical operation, conditions can change by the minute, and natural occurrences, such as sand blowing or debris flying, can impact performance and data fidelity. As well as having the capacity to operate autonomously in harsh, remote locations (collecting data in isolation or in a mesh with several receivers), the deployed solution must be ruggedized and comprise the necessary backhaul and processing power to enable real-time signal sampling at source for efficiency and TDPA reasons.  

An automated solution operating in hostile conditions gives military forces, for example, a tactical advantage by allowing them to detect, measure, and monitor RF signals quickly. As such, they can determine the following: 

• Who or what is generating the RF signals 
• Where they are coming from (geolocation) 
• What counteraction is needed  

Conclusion 

RF monitoring is a critical tool for emergency response and military missions. To achieve the data fidelity levels needed for accurate signal sampling in mission-critical situations, only automated monitoring systems can transform the captured information into actionable intelligence—ensuring successful outcomes.