A methodology for signals intelligence using non-conventional techniques and software-defined radio

This article focuses on M15 organization and Klaus Fuchs, a German-born physicist and Soviet “Atom Spy” who was arrested in 1950 and served fourteen years for offences related to atomic espionage. It examines how Fuchs was identified as an “Atom Spy” in 1949 and describes the MI5's investigation, which ended in the early 1950 with the successful arrest, prosecution, and imprisonment of this highly significant Cold War figure. Key issues discussed in this article include the difficulties encountered by MI5 and the budding British atomic program in the sphere of security. It also discusses the role of Signals intelligence (SIGINT) in the investigation of Fuchs, and the high-risk but ultimately successful approach taken by MI5's key interrogator, William Skardon. This case study highlights both the unparalleled level of international intelligence cooperation between the British agencies and their American counterparts, which made the resolution of this case possible, and some of the frailties in the Anglo-American alliance that were brought to the fore by the exposure of Fuchs as an Atom Spy.

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The Troubled Inheritance: The National Security Agency and the Obama Administration

The Oxford Handbook of National Security Intelligence ◽

10.1093/oxfordhb/9780195375886.003.0015 ◽

2010 ◽

pp. 241-256

Author(s):

Matthew M. Aid

Keyword(s):

Data Processing ◽

National Security ◽

Bush Administration ◽

Intelligence Community ◽

National Security Agency ◽

Obama Administration ◽

Policy Issues ◽

The U.S ◽

The Coordinator ◽

Signals Intelligence

This article discusses the National Security Agency under the Obama Administration. Upon his inauguration on January 20, 2009, Obama inherited from the Bush administration an intelligence community embroiled in political controversies. Of the sixteen agencies of the intelligence community, the National Security Agency (NSA) faced the greatest scrutiny from the new Obama administration and the Congress. NSA was the largest and the most powerful member of the U.S. intelligence community. Since its formation in 1952, NSA has managed and directed all U.S. government signals intelligence (SIGINT) collection. It is the collector and processor of communications intelligence (COMINT) and the primary processor of foreign instrumentation signals intelligence (FISINT). And since 1958, NSA has been the coordinator of the U.S. government's national electronics intelligence (ELINT) program. It has also the task of overseeing the security of the U.S. government's communications and data processing systems, and since the 1980s, NSA has managed the U.S. government's national operation security (OPSEC) program. In this article, the focus is on the challenges faced by the NSA during the Bush administration; the role played by the NSA during the wars in Afghanistan and Iraq; and the challenges faced by the Obama administration in confronting a series of thorny legal and policy issues relating to NSA's eavesdropping program.

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Active-RC channel selection filter tunable from 6kHz to 18MHz for software-defined radio

2005 IEEE International Symposium on Circuits and Systems ◽

10.1109/iscas.2005.1465707 ◽

2005 ◽

Cited By ~ 4

Author(s):

Jin-Hong Hwang ◽

Mi-Young Lee ◽

Chan-Young Jeong ◽

Changsik Yoo

Keyword(s):

Software Defined Radio ◽

Channel Selection

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Intelligent Non-Contact Sensing for Connected Health Using Software Defined Radio Technology

Electronics ◽

10.3390/electronics10131558 ◽

2021 ◽

Vol 10 (13) ◽

pp. 1558

Author(s):

Muhammad Bilal Khan ◽

Mubashir Rehman ◽

Ali Mustafa ◽

Raza Ali Shah ◽

Xiaodong Yang

Keyword(s):

Psychological Health ◽

Software Defined Radio ◽

Orthogonal Frequency Division Multiplexing ◽

Additive White Gaussian Noise ◽

Vital Signs ◽

Wireless Channel ◽

Machine Learning Algorithms ◽

Breathing Patterns ◽

Connected Health ◽

Innovative Solution

The unpredictable situation from the Coronavirus (COVID-19) globally and the severity of the third wave has resulted in the entire world being quarantined from one another again. Self-quarantine is the only existing solution to stop the spread of the virus when vaccination is under trials. Due to COVID-19, individuals may have difficulties in breathing and may experience cognitive impairment, which results in physical and psychological health issues. Healthcare professionals are doing their best to treat the patients at risk to their health. It is important to develop innovative solutions to provide non-contact and remote assistance to reduce the spread of the virus and to provide better care to patients. In addition, such assistance is important for elderly and those that are already sick in order to provide timely medical assistance and to reduce false alarm/visits to the hospitals. This research aims to provide an innovative solution by remotely monitoring vital signs such as breathing and other connected health during the quarantine. We develop an innovative solution for connected health using software-defined radio (SDR) technology and artificial intelligence (AI). The channel frequency response (CFR) is used to extract the fine-grained wireless channel state information (WCSI) by using the multi-carrier orthogonal frequency division multiplexing (OFDM) technique. The design was validated by simulated channels by analyzing CFR for ideal, additive white gaussian noise (AWGN), fading, and dispersive channels. Finally, various breathing experiments are conducted and the results are illustrated as having classification accuracy of 99.3% for four different breathing patterns using machine learning algorithms. This platform allows medical professionals and caretakers to remotely monitor individuals in a non-contact manner. The developed platform is suitable for both COVID-19 and non-COVID-19 scenarios.

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Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory (Spanish Pyrenees) During the 2019/2020 Winter Season Using a Stepped-Frequency Continuous Wave Radar (SFCW)

Remote Sensing ◽

10.3390/rs13040616 ◽

2021 ◽

Vol 13 (4) ◽

pp. 616

Author(s):

Rafael Alonso ◽

José María García del Pozo ◽

Samuel T. Buisán ◽

José Adolfo Álvarez

Keyword(s):

Software Defined Radio ◽

Continuous Wave ◽

Snow Water Equivalent ◽

Cosmic Ray ◽

Relative Dielectric Permittivity ◽

Near Surface ◽

Wave Radar ◽

Spanish Pyrenees ◽

Snow Water ◽

Stepped Frequency

Snow makes a great contribution to the hydrological cycle in cold regions. The parameter to characterize available the water from the snow cover is the well-known snow water equivalent (SWE). This paper presents a near-surface-based radar for determining the SWE from the measured complex spectral reflectance of the snowpack. The method is based in a stepped-frequency continuous wave radar (SFCW), implemented in a coherent software defined radio (SDR), in the range from 150 MHz to 6 GHz. An electromagnetic model to solve the electromagnetic reflectance of a snowpack, including the frequency and wetness dependence of the complex relative dielectric permittivity of snow layers, is shown. Using the previous model, an approximated method to calculate the SWE is proposed. The results are presented and compared with those provided by a cosmic-ray neutron SWE gauge over the 2019–2020 winter in the experimental AEMet Formigal-Sarrios test site. This experimental field is located in the Spanish Pyrenees at an elevation of 1800 m a.s.l. The results suggest the viability of the approximate method. Finally, the feasibility of an auxiliary snow height measurement sensor based on a 120 GHz frequency modulated continuous wave (FMCW) radar sensor, is shown.

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