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Real-time Digital Signal Processing for Electronic Warfare Systems

The advancement of Sensors, Communications and Radars have given rise to Electronic Warfare, which encompasses, in all battle phases, military actions involving the use of EM energy to determine, exploit, reduce or prevent hostile use of EM spectrum and the actions, which retain friendly use of the EM spectrum. Understanding and managing, and if necessary, controlling and denying the electromagnetic spectrum are as critical for national defense as an army, navy, air, or space force.

 

Electronic warfare  employs directed radiofrequency energy – ranging from radio signals through radar, up to lasers and beyond – to manipulate, control, or even destroy an adversary’s ability to effectively use the electromagnetic spectrum. Electronic warfare uses the spectrum to gain and maintain military access to the spectrum. Electronic warfare (EW) is any action involving the use of the electromagnetic spectrum or directed energy to control the spectrum, attack of an enemy, or impede enemy assaults via the spectrum. The purpose of electronic warfare is to deny the opponent the advantage of, and ensure friendly unimpeded access to, the EM spectrum. EW can be applied from air, sea, land, and space by manned and unmanned systems, and can target humans, communications, radar, or other assets.

 

Electronic warfare contains offensive and defensive capacities, from preemptive targeting and spoofing, to countermeasures against adversary EW.

 

Electronic Warfare Technology refers to any action involving the use of electromagnetic waves to sense, detect, locate, track and communicate with systems on air, land or water. Electronic Warfare solutions use focused energy, electromagnetic signals such as radio or infrared to sense, track, or communicate. Electronic warfare systems are also used to disrupt communication through signal interference in their environment. Electronic Warfare systems can also be used to either disrupt or use these signals.

 

Electronic warfare systems have three main capabilities: sensing the environment (sense and collect), analyzing the environment (signal analysis), and responding to the environment (response technique and high power transmission). EW can be broadly classified into three major categories – Ground-based EW, Surface EW and Airborne EW. Mistral provides cutting-edge solutions for all the above-mentioned categories.

 

Whether the mission is to intercept and collect, analyze, or counter, the many wireless signals that crowd the electromagnetic spectrum (EMS) – a combination of new technology trends – is increasing the probability of earlier detection, assessment, and response. The EMS on an electronic battlefield is chaotic and complex; the ability to fully understand signal behavior in a real-world environment is crucial in the design and validation of the latest radar, electronic warfare (EW), and signals-intelligence (SIGINT) systems.

 

Electronic Warfare technologies

In electronic warfare systems, key drivers for continuous enhancements are electronic counter-counter-measures (ECCM), stealth technologies, closely interlinked smart sensor networks, and intelligent guided weapons. Modern autonomous threat sensors can readily detect and locate targets by incorporating state-of-the-art high-speed digital signal processing (DSP) algorithms that focus on the classification of targets via target physical features.

 

The success of future Electronic warfare missions shall require development of many technologies like, fast and powerful ESM processors to handle and track multimode radars in a millions of pulses per second dense scenario, very high sensitivity channelized digital receivers to detect intercept (LPI) radars, phase interferometry DF, amplitude comparison DF and TDOA techniques, Multi sensor data fusion.

 

DSP technology uses specially designed programs and algorithms to manipulate analog signals and produce a signal that is higher-quality, less prone to degradation or easier to transmit. Digital Signal Processors (DSP) take real-world signals like voice, audio, video, temperature, pressure, or position that have been digitized and then mathematically manipulate them. Signals need to be processed so that the information that they contain can be displayed, analyzed, or converted to another type of signal that may be of use.

 

Real-time requirements

Radar, electronic warfare (EW), and signals-intelligence (SIGINT) systems face new challenges from near-peer threats, requiring multigigahertz bandwidths, nanosecond latencies, and the ability to implement and field new EW techniques – all of them needed to deploy in seconds or minutes, not days or months.

 

The challenge of signal processing for electronic warfare and signals intelligence applications revolves around the sequence of events that happen in transforming raw RF signals at an antenna into useful information for fighting forces to use as they take some sort of action. To be effective, this sequence must be fast and efficient in converting signals from analog to digital, and filter out noise and other irrelevant RF energy, while processing data quickly to pull out the most important information from a flood of data.

 

One of the challenges for the Army’s science and technology community is that the electromagnetic spectrum is “very dense,” and adversary systems operating in different frequency bands make them difficult to track. “Our ability to be able to detect those RF emissions, sense them, understand them at a rapid speed at the pace of operation is challenging,” Taylor says.

 

The Army is working on fielding several other new EW capabilities using the increase in processing power. The Electronic Warfare Planning and Management Tool for visualization is nearing maturity, as are the Terrestrial Layer Systems for EW and cyber. The former is a mission planning tool that maps out the military and commercial electromagnetic environment, while the latter is a planned vehicle-mounted platform.

 

EW gaining greater processing power means sensors that can “have increasingly broad, instantaneous bandwidth for much faster processing and greater awareness,” Brent Toland, sector vice president and general manager for the navigation, targeting and survivability division at Northrop Grumman Mission Systems, told Breaking Defense this April.

 

Cognitive Radio

 

Cognitive is a term being used to describe next-generation radio and EW technology. What capability does the cognition bring and how does embedded signal processing enable it?

 

If you’re talking about cognitive radio, you’re talking about the ability to understand the surrounding environment, autonomously determine friendly signals from enemy signals, detect potential jamming efforts, and then maneuver transmissions to different frequencies to avoid the jamming attack. Often such operations are also termed “adaptive radio.” Because the enemy is always trying to deny communications and their efforts are becoming more sophisticated, cognitive radios need to have the capability to be a step ahead of the enemy and always improving over time, said HOSKING.

 

Cognitive systems can react more quickly than humans and therefore counter the jamming attacks to restore the communications link with minimal downtime to stay one step ahead of any potential adversaries. A similar approach is being used for cognitive EW, where the cognitive EW system becomes more intelligent and agile in adapting to threats and interference.

 

Data Mining

Data Mining for exploration and analysis on large amounts of data in order to discover patterns of interest will depend on enabling technologies like Machine Learning, Support Vector Machines (SVM), Artificial Neural Networks (ANN),  Self Organising Neural Networks (SONNs) or Unsupervised Neural Networks, Fuzzy  neural networks.

 

These systems must be able to rapidly analyze and respond to multiple threats in very short time frames. In attempting to find target signatures in broadband noise, architects are seeking to perform complex processing such as fast Fourier transforms (FFTs), Cholesky decomposition, and matrix multiplication.

 

For radar systems larger Fast Fourier Transforms (FFTs) are needed for more precise Doppler processing, where the radar systems track the speed and direction of targets. Improving resolution at a given range yields more accurate target information, including the size of an aircraft and detection of unique surface structures and reflection characteristics of a jet. This rich set of information in the received signal can help identify a unique target. It’s akin to looking at a fingerprint 10 feet away vs. examining it under a microscope.

 

Radar waveforms also get more complicated every year as military system designers want better algorithms to glean more information and to improve signal to noise performance so they can extract targets from clutter and noisy environments.

 

Multiple software-generated waveforms are then transmitted to provide false targets, while powerful wideband signals provide overall cover. These shifting tactical responses require agile, high-performance processing. The entire system frequently resides in an airborne platform and must meet strict requirements for heat dissipation along with size, weight, power, and cost (SWaP-C) constraints.

 

A typical system design, uses a channelizer and inverse-channelizer to process high-bandwidth input signals. The number of channels are flexible so system designers can allocate hardware resources versus system performance as needed.

 

The military wants wider bandwidth to handle the latest spread spectrum signals and more channels to handle increased traffic. Key goals are improving classification of radio types, boosting transmission range and noise immunity, and enhancing signal detection and exploitation. To achieve this, they need faster data converters to handle the multi-gigahertz sampling rates to digitize these wideband signals. This, in turn, means more digital signal-processing resources to perform the required algorithms in real time, a task ideally suited to the thousands of DSP blocks in FPGAs, all running in parallel, says Rodger Hosking, Vice President and Co-founder of Pentek

 

FPGAs offer an ideal solution to these performance requirements in the critical high-speed processing-intensive paths, a typical electronic warfare system with different electronic attack (EA) techniques.

 

Faster embedded system links are also in demand between data converters and FPGAs as well as higher data rates between boards within a chassis and higher data rates between systems and sub-systems. As digitizers and front-end DSP operations move closer to the sensors faster data transmission paths to these distributed acquisition sub-systems are necessary.

 

Reconfigurable FPGA-based signal processors, optical streaming interfaces based on the Optical Data Interface (ODI) standard, and low-overhead packet standards based on the VITA Radio Transport (VRT) specification, combine to deliver unprecedented performance and flexibility. These three new technologies converge to enable a new class of software-defined operational and measurement systems that are able to address these new challenges.

 

Test and Evaluation

Increasingly complex and diverse threats are driving the need for future EW ­systems to identify and neutralize these adaptive radar signals with cognitive countermeasures. As the EW threat environment continues to evolve, confidence and reliability in EW system validation and verification depends on improvements and modernization in the test and evaluation process.

 

There are several significant measurement challenges, however. First, the signals of interest are highly unpredictable, making them difficult to capture and recreate using traditional measurement methods. Fortunately, the latest digital hardware, processing engines, and interfaces enable the creation of RF [radio frequency] streaming solutions that can analyze, record, and play back signals for seconds, minutes, hours or even days. Another challenge is the resulting mountain of “Big Data”: Dealing with a glut of data calls for an optimized combination of measurement hardware and software, which can accelerate the data collection and make the analysis more manageable.

 

Evaluating and characterizing wideband communications, radar and electronic warfare systems in real time is challenging. Lacking a commercial off-the-shelf (COTS) alternative, some radar test teams stream test data to an inherently non-deterministic computing device such as a PC or laptop, inevitably leading to lost or missing data with no ability to verify that data is being recorded as expected.

 

Applications such as radar target simulation and emulation require complex signals with frequency shift, delay, and channel effects. These signals have typically been generated and analyzed with digital signal processing engines or recorded to and played back from a deep-memory storage device such as a RAID [redundant array of independent disks].

 

 

References and Resources also include:

https://www.militaryaerospace.com/computers/article/14281585/the-sensor-and-signalprocessing-challenges-of-electronic-warfare

https://militaryembedded.com/radar-ew/signal-processing/fpgas-fuel-military-electronic-warfare-cognitive-radio-and-radar-signal-processing-innovation

https://militaryembedded.com/radar-ew/addressing-the-data-challenges-of-modern-electronic-warfare-and-radar

About Rajesh Uppal

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