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DARPA developing cognitive radio IC technology for next-gen Communications, Radar, and Electronic Warafre

The U.S. Defense Advanced Research Projects Agency (DARPA) and British defense firm BAE Systems have developed a new lightweight, handheld tactical sensor that lets U.S. soldiers easily detect and identify enemy electronic jammers on the battlefield.


During Recent ongoing Syrian conflict Russia has demonstrated many advanced weapons, one of which were advanced electronic warfare systems. U.S. Air Force Gen. Philip Breedlove, commander of U.S. European Command told the House Armed Services Committee: “They [Russians] have invested a lot in electronic warfare because they know we are a connected and precise force and they need to disconnect us to make us imprecise.” During his testimony, Breedlove admitted that the Pentagon had neglected electronic warfare during the past two decades—which has allowed the Kremlin to gain an advantage.


Recently, the Pentagon seems to be refocusing on electronic warfare. The vice-chairman of the Joint Chiefs of Staff is mulling the possibility of designating the electromagnetic spectrum as a warfighting domain—like the air, sea or land.  DARPA’s Computational Leverage Against Surveillance Systems (CLASS) program seeks new ways to protect their signals from increasingly sophisticated adversaries and to do so in a way that can be maintained as technology advances.  The objective of the CommEx is to enhance the communication of friendly forces within a congested jamming environment by suppressing enemy jamming with “adaptive interference suppression”


The objective of the program is to make modular communications technology that is inexpensive to incorporate in existing and emerging radio systems (<$100 incremental cost) but pushes adversaries to need more than 1,000x our processing power – “supercomputer” level processing power.


The aim is to develop cognitive  system that  is aware of its external environment and internal states, such as the electromagnetic/signal environment in the case of cognitive RF systems, and can autonomously decide and adjust its behavior to optimize quality of service or other operational objectives. Signal parameters of interest include modulation schemes, signal constellations, multiple access or hopping schemes, channel utilization and demodulated symbols.


DARPA envisions that this goal will be achieved by investigating and developing novel RF, analog and mixedsignal integrated circuit architectures and design techniques. The goal of CLASIC is to enable monolithic, high performance, ultra high energy efficiency, signal recognition integrated circuits (ICs) for next-generation military microsystems in areas such as cognitive communications, radar and electronic warfare.


DARPA awarded CommEx contracts to BAE Systems Company in 2011 to develop adaptive communication technologies under intense jamming, which blocks the RF receivers of military aircraft. The company worked on the project until 2015, when it demonstrated the benefits of the CommEx in a laboratory environment .Currently, the test and demonstration phase is nearly finalized. The CommEx technology is planned as an upgrade to the Link 16 air-to-air data-exchange network, which is used by several nations, According to DARPA, the CommEx will fix the vulnerability of the Link 16 network to enemy jamming. If the program passes the testing phase, the CommEx will be installed on aircraft to upgrade the Link 16 network.


Traditionally, signal recognition functions have been implemented in digital electronics, including FPGAs and DSPs. In conventional signal recognition system, where RF signals are down-converted, digitized and correlated against a library of known signals in order to determine waveform parameters. In commercial wireless communications systems, where a known set of established communications standards are involved, this process can be done quite efficiently.


However, in military systems, excessive amounts of energy are typically expended in the waveform correlation process due to the potentially large numbers of waveforms of interest, as well as significant power for the A/D conversion process in the case of wide analysis bandwidths of interest. Alternative classification approaches, such as those based on cyclostationary statistic computation and analysis, likewise require large amounts of energy because of the high computational complexity of the underlying algorithms.


Efficient signal processing techniques for separating and decoding mixtures of complex signals are needed. DARPA envisions that, in combination with architectural innovations, analog signal processing techniques may provide significant improvements in effective MIPS/mW with respect to state-of-art DSP/FPGA techniques.



BAE Systems Reveals Handheld Cognitive Electronic Warfare Technology for DARPA

Through a contract from the U.S. Defense Advanced Research Projects Agency (DARPA), BAE Systems has developed a new lightweight, handheld tactical sensor that soldiers can easily carry and use to better understand radio frequency (RF) signals for enhanced situational awareness.


A statement from the company says that the new device “can quickly detect and identify multiple interfering signals, such as jammers or enemy communication signals, across a wide spectrum and in changing and challenging environments.”The new capability can be leveraged across multiple platforms and can integrate, for example, into a variety of EW, SIGINT, and signal receiver and communication systems, both large and small.


By drastically reducing the size, weight, and power of this new cognitive EW system, we’re making it easier for our warfighters to be aware of, classify, and manage a wide range of signals in the battlespace, which is crucial for tactical situational awareness,” said Joshua Niedzwiecki, director of Sensor Processing and Exploitation at BAE Systems. “Better situational awareness on the battlefield means superior protection for our troops and a greater ability to defeat hostile threats.”


The new system relies on artificial intelligence techniques and machine learning to work in real time. During recent field tests, the new technology successfully detected and identified more than 10 signal types across a wide bandwidth in the presence of interference. The company expects to continue to mature this technology for eventual deployment within its EW, SIGINT, and tactical communications portfolios.


The technology was developed under DARPA’s Computational Leverage Against Surveillance Systems (CLASS) program and the Cognitive radio Low-energy signal Analysis Sensor ICs (CLASIC) program. This new handheld EW capability improves on today’s portable spectrum analyzers, which are often bulky, power hungry, and unable to handle interference or classify the signals they detect. Using advanced signal processing algorithms, BAE Systems radically reduced the time and the computing power needed to process detected signals to such an extent that the new system uses only one low-power chip. The result is a 10-times reduction in size, weight, and power compared to conventional spectrum analyzers.



The CLASS program (Computational Leverage Against Surveillance Systems) seeks a special type of communications system that provides high protection from adversary’s Detection, Interception and Exploitation of its signals. While these Electronic protection(EP) mechanisms may reduce other desirable attributes of a communication system such as throughput, spectral efficiency, network performance or latency, the goal of the CLASS program is to minimize the degradation of communications capability while enhancing the signal protection.


The CLASS program will create new communications waveforms and communication methods that leverage computational capability in signal processing. CLASS will leverage superior signal processing techniques to enable us to receive and process our transmissions using sophisticated Application Specific Integrated Circuits (ASICs) while forcing adversaries to require “supercomputing” class processing resources to exploit our signals. The CLASS program is not about creating a new radio, rather, DARPA seeks to develop modular technology that can be incorporated into existing and planned radio systems.


The operating scenario the CLASS technology seeks to address includes ground-ground, ground- air,and air-air operations. The example scenarios are:

Ground-Ground: Squad communications to platoon leadership or convoy to base
Ground-Air: Close Air Support coordination with fixed wing or rotary aircraft or UAV operation.
Air-Air Operations: Coordination communications between clusters of aircraft or refueling operations.

For the CLASS program, DARPA is concentrating on six technical areas: waveform complexity; spatial diversity techniques; interference exploitation; technology integration; modular product development; and radio integration.

Waveform complexity

Waveform Complexity has been used in spread spectrum communication systems for many years, but the techniques that have been used are limited by the processing power that was available at the time of development. Spread-spectrum telecommunications is a signal structuring technique in which a telecommunication signal is transmitted on a bandwidth considerably larger than the frequency content of the original information. The receiver correlates the received signals to retrieve the original information signal. These can be direct sequence, frequency hopping, or a hybrid of these allow resistance to enemy efforts to jam the communications (anti-jam, or AJ), or to hide the fact that communication was even taking place, sometimes called low probability of intercept (LPI). Each of these techniques employs pseudorandom number sequences — created using pseudorandom number generators — to determine and control the spreading pattern of the signal across the allocated bandwidth.


This program seeks to use similar or enhanced techniques with sophistication matched to the processing power available in today’s processors or new techniques that will increase the difficulty in recovering a signal without a priori knowledge of the signal. Proposed techniques could involve removing predictable structure from communication waveforms, add atypical random structure, explore new methods of acquiring or tracking signals, or other techniques that are likely to create an asymmetry in the processing power required by an unintended receiver compared to an intended receiver.

Spatial Diversity

Spatial diversity refers to manipulating the spatial characteristics of a signal to create controlled, easily recovered waveforms at the destination receiver while creating difficult-to-recover signal characteristics at other locations.


Distributed Multiple Input Multiple Output (MIMO) communication techniques, where multiple, separately located apertures are used to create a transmit signal, are of particular interest. Issues to be addressed include the synchronization of individual transmitters and the efficient distribution of processing resources between receiver nodes.


Other techniques and operational concepts that exploit the spatial distinction between the intended and unintended receivers will be considered.Three types of interrelated effects are sought – 1) transmissions from multiple spatially distributed locations to obscure the location of the transmission to an unintended observer, 2) reduction of signal power of any one transmitter for a specific range to make an individual transmitter harder to receive and to reduce battery drain, 3) range can be increased through the use of multiple simultaneous transmissions.


Interference Exploitation

Interference Exploitation techniques seek to use natural and artificial interference against an unintended receiver. For example, an intended receiver may be able to receive a signal in the presence of interference because it understands the nature and characteristics of the source and can focus processing resources on the source signals. An unintended receiver must dedicate processing resources to both source signal and to the excision of the interference.


Technology integration refers to developing CLASS technology in modular form for integration into existing and planned military radio systems. Modular product development seeks to blend CLASS technology into existing military radios as technology modules. The host radio will communicate with the module through a standards-based digital interface and the module will provide an RF signal that may be transmitted independently or be multiplexed with the host radio signal.


Radio integration, meanwhile, seeks to integrate CLASS technology into other radio systems as a hardware/software/firmware technology suite.


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