This article explores the capabilities of SDRs that make them suitable for developing solutions for securing critical facilities. We discuss various solutions including wireless-based perimeter security systems, also known as virtual-fence systems, that are becoming common due to the availability of low-power internet of things (IoT) sensors. In addition, we extensively explore the capabilities of SDRs in monitoring sources of interference and jamming signals in critical facilities.

Critical Facility Security Challenges Difficult topographical conditions is one of the main challenges encountered by national border protection units. In mountainous and forested locations, human surveillance of borders is less effective and does not guarantee complete protection. The only solution that can ensure complete protection in such areas is a smart system that is capable of monitoring and immediately reporting breaches.

Monitoring the security of solar farms is challenging because they are usually located in isolated areas and distributed over vast geographical areas. Remote supervision offers a cost-effective and efficient way of monitoring dispersed power plants. Figure 1 above shows a solar power plant located in an isolated location.

There are many cases of prisoners escaping or attempting to escape from prison reported every year. This means that incarcerating prisoners requires more than just a single physical fence and locked cells. Perimeter protection offers a broad array of solutions that help to prevent various illegal activities in a prison such as tunneling and digging. Often, it is the use of contraband cellphones and unauthorized transmissions in prisons that are used for planning illegal activities within and outside a facility. Using a smart system that is capable of detecting such communications can greatly boost security both within prisons and outside.

Most metropolitan airports have strict timing requirements that leave little room for delays and errors. RF aviation communications in such busy airports are critical and any disruption can seriously affect runway activities and air traffic patterns. It is therefore vital for such airports to have a system that is capable of preventing illegal use of air traffic control (ATC) frequencies.

Securing Perimeters A buried seismic intrusion detection system offers an additional protection layer to existing solutions such as fences and radar systems. Using several layers of perimeter security systems to protect a border enhances the overall level and reliability of security.

A typical perimeter fence system comprises a hub unit and smart seismic sensors. The sensing elements and the processing capabilities of the system are usually fully distributed. Each sensor features a digital signal processing (DSP) processor that performs local sampling and processing. Some perimeter fence systems utilize wireless sensors that send acquired data to a hub.

Most perimeter fence systems use the Institute of Electrical and Electronics Engineers (IEEE) 802.16s industrial wireless standard. The coverage offered by this standard allows implementation of perimeter fences for securing borders and other critical facilities at a reasonable cost.

In order to maximize the level of security, perimeter fences utilize sensors that use adaptive self-learning algorithms. This advanced technology offers a high level of threat detection and recognition. Unlike traditional systems, these sensors can precisely distinguish between various types of intrusions. Furthermore, buried perimeter intrusion detection (PID) systems are capable of recognizing underground activities caused by small animals thereby significantly minimizing false alarm rate (FAR).

Securing with Spectrum Monitoring Spectrum monitoring is commonly used as the first line of defense in preventing unauthorized transmissions in restricted areas. It is also widely used for many other functions including characterizing RF emissions, determining spectrum availability, continually monitoring critical bands to prevent unauthorized use, managing regulated spectrum and detecting illegal transmissions.

Some of today's RF signals have unique characteristics that make it difficult for engineers and scientists to detect and characterize them with traditional spectrum analyzers. For tasks involving such signals, it is necessary for spectrum monitoring teams to employ advanced tools such as real-time spectrum analyzers (RSAs).

As the spectrum becomes more congested, spectrum monitoring is increasingly becoming a critical tool for detecting and characterizing illicit sources of transmission in government, as well as private facilities and protecting intellectual property and sensitive information from unauthorized parties.

There are various types of spectrum monitoring including close proximity monitoring, continuous monitoring and distributed network monitoring. Alarms and triggers are used to alert spectrum monitoring teams when a suspected source of illicit transmission is detected. Spectrum monitoring units mostly utilize swept signal analyzers and real-time signals analyzers to monitor wide bandwidths of spectrum.

The raw data that is captured during a spectrum monitoring exercise is usually recorded in server system storage solutions for further processing and analysis. In cases where an SDR-based monitoring solution is used, this data is in the form of IQ pair data. Recording these vast amounts of raw data is usually achieved by utilizing Ethernet protocols.

Playback and data analysis refer to the processes of identifying and characterizing signals of interest from recorded data. Various software suites and DSP techniques including discrete Fourier transform, DFT, inverse DFT (IDFT) and spectrograms are used in this stage.

Spectrum Monitoring Specifications One of the most important specifications of a signal analyzer is the frequency range or coverage. This parameter is mainly determined by the specifications of the local oscillator, as well as the center frequency of the intermediate frequency (IF) filter. High-end signal analyzers usually have a wide frequency coverage.

The marker resolution of a fast Fourier transform (FFT) analyzer refers to the step size that the marker is capable of making. It is a measure of the step between two adjacent positions and is usually given in hertz.

The phase noise of a signal analyzer is specified as the single sideband noise that would be measured using an ideal signal source. It is usually given in decibels relative to carrier (dBc).

The resolution bandwidth of a signal analyzer refers to the ability of a device to separate and measure two adjacent signals. The bandwidth of a filter is one of the key parameters that determine the resolution bandwidth of a signal analyzer.

The data captured by a signal analyzer is stored in a storage solution for further processing and analysis. Some of the key specifications that determine the overall performance of a storage solution include the drive space, data rate and the method of data transfer. A lossless data transfer method ensures minimal dropping of data packets.

SDRs in Spectrum Monitoring and Virtual Fence Solutions An SDR is a flexible radio system that consists of a radio front-end (RFE) and a digital backend. The RFE performs transmit (Tx) and receive (Rx) functions and can handle signals over a wide frequency range, typically 0 – 18 GHz. The highest-bandwidth SDR systems can be customized to provide an extended tuning range, usually up to 40 GHz.

The digital backend of a high performance SDR system features a field programmable gate array (FPGA). This module has a variety of on-board DSP capabilities including upconverting, down-converting, modulation, demodulation and data packetization over Ethernet. Furthermore, this module is reconfigurable and allows implementation of new radio protocols and DSP algorithms at a low cost. Moreover, SDR platforms offer multiple TX and RX channels with dedicated analog-to-digital converters (ADC) and digital-to-analog converters (DACs).

Since vast amounts of data are captured during spectrum monitoring, it is usually necessary to pair SDRs with high performance storage solutions. Some applications such as virtual fence networks involve capturing data from many sensors that are dispersed. The capabilities of an SDR platform make it suitable for use as a hub or gateway in such applications.

Data loss issues can complicate the process of transferring data from an SDR to a host system. This complexity increases with an increase in the number of sensors used in data collection, as well as the amount of data. For instance, it is usually difficult to reliably transfer the huge amounts of data captured in wideband spectrum monitoring.

Reliable and fast transfer of data from an SDR platform to a host system requires a high performance network interface card (NIC). 10G, 40G, 100G or PCIe NICs are usually used for such applications. Using FPGA-based NICs helps to prevent data loss caused by packet dropping. NVMe SSDs are commonly used in the highest-throughput SDR systems to ensure that maximum throughput is achieved. In addition, proper RAID configuration is required to ensure that data is read and written at optimal speed. Figure 2 shows a block diagram of an SDR system with storage solution.

The capability of SDR systems to operate over a broad range of frequencies makes them suitable for applications involving scanning wide bandwidths for illicit transmissions. This property also makes them suitable for use as real-time spectrum analyzers (RTSAs) for monitoring wide bandwidths. Moreover, the flexibility of SDR platforms makes them suitable for implementing cognitive radio solutions for use in research and development of advanced spectrum sharing technologies. In addition, the capability of SDR systems to measure power levels makes them ideal for monitoring the power levels emitted by sources to ensure that they do not exceed the maximum limit.

Spectrum recording enables identification of offending signals and their geolocations. Highest storage capacity recorder systems are capable of storing vast amounts of raw data for later processing and analysis. Best performance spectrum monitoring receiver systems are equipped with high speed digital backhauls to allow high speed data transfer. 40G and 100G digital backhauls are commonly used in the highest data capture recorder systems.

An SDR system can be used as a hub in systems containing a wide variety of sensors. In such applications, the SDR can be used for many functions including wireless communications, data transfers over Ethernet connections, and more.

SDR Benefits There are many benefits of using SDR systems in spectrum monitoring and perimeter fence applications. To begin with, these devices have multiple channels and offer wide tuning ranges and wide bandwidths. Highest channel count SDR systems are capable of monitoring all frequencies of interest in real time and communicating with large numbers of sensors.

The high interoperability of SDR devices enables them to work with existing legacy systems as well as the latest technologies. This makes them suitable for use in both service life extension programs (SLEP) and new deployments in applications such as airport traffic control systems and mobile network infrastructure.

SDR systems offer a high noise figure and spurious-free dynamic range (SFDR) which makes them suitable for detecting sources of interfering or jamming signals. Moreover, the on-board DSP resources available on FPGAs enable a wide range of operations to be performed including filtering, FFT, compression and power measurements.

The upgradeability and reconfigurability of SDR platforms means that a single unit can be used for different spectrum monitoring functions. Furthermore, this flexibility also allows new wireless communication standards and wireless sensors to be added with ease.

Protecting today's critical facilities such as airports, power plants and prisons requires smart solutions that are capable of delivering high reliability. The performance characteristics of SDR platforms make them suitable for implementing spectrum monitoring and virtual fences solutions for protecting critical facilities from illicit transmissions and illegal activities. In addition, the flexibility of these platforms allows new wireless protocols, DSP algorithms, and additional nodes to be added at a reasonable cost.

Brendon McHugh is a field application engineer and technical writer at Per Vices. Per Vices specializes in building and deploying high performance SDR systems that are suitable for spectrum monitoring and recording applications and developing hubs for wireless sensors.

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