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Distributed, Large Scale Spectrum Measurement and Analysis

Description:

 
 

PROPOSALS ACCEPTED: Phase I and DP2. Please see the 16.2 DoD Program Solicitation and the DARPA 16.2 Direct to Phase II Instructions for DP2 requirements and proposal instructions.

TECHNOLOGY AREA(S): Electronics, Information Systems

OBJECTIVE: Develop and demonstrate innovative methods to collect, process, and analyze RF spectrum measurements made from a large number (50 or greater) of mobile collection platforms (at low altitude and/or close to the emitters) to obtain useful information on spectrum use and activities.

DESCRIPTION: There is a critical DoD need to obtain radio operations information using spectrum measurements. The Internet of Things devices and the proliferation of low power communication devices are becoming an increasing factor in wireless operations. Many of these systems use directional signals and operate at high frequencies. These factors make these signals unobservable at large standoff distances. In cases where these signals are detectable, the number of signals detected tends to overwhelm any signal processing system.

It is of interest to use large (10s to 100s) numbers of small, low cost platforms to carry a small spectrum collection and processing sensor to provide distributed, wide area coverage for spectral sensing and radio operation understanding. This would solve both the problems of making an individual system “disposable” and detecting weak signals possible. There are other advantages such as spatial diversity detection (receiving signals simultaneously from many spatial angles), location diversity (seeing signals from many locations), etc. The platforms of interest can include airborne and ground platforms.

The challenge is that a mobile platform near a transmitter or flying at low altitudes (to avoid detection) measures a signal with rapidly varying amplitudes and small detection distance. Combining these problems with uncertain or unknown transmitter parameters (duty cycle, antenna pointing angle, antenna beam motion, waveform agility, etc.) makes mobile platform spectrum data interpretation very difficult. Another challenge is that small mobile platform sensors have limited spectrum scan rate, processing, and backhaul capabilities. These limitations need to be managed to achieve useful mission selectable goals.

PHASE I: Develop a system design concept, including the sensor platform, networking approach, and application functionality. Perform technology risk reducing experiments and demonstrations of system components if possible. Develop algorithms and software to enable obtaining useful information on transmitters (characteristics, locations, mobility, etc.) from the distributed measurements.

PHASE II: Develop, demonstrate, and validate a prototype distributed mobile spectrum measurement system. The prototype should focus on mobile airborne platforms, but the demonstration may involve live ground platforms along with emulated data from airborne sensors for cost efficient tests. The demonstration should include real and emulated sensors to show scalability (goal of 50 nodes).

PHASE III DUAL USE APPLICATIONS: Commercial applications: Continue to mature the design by adding features to meet requirements for commercial applications in spectrum monitoring and enforcement in industries such as telecommunications and broadcasting. The testing should include common commercial UAV platforms.

DoD/Military applications: Continue to mature the design by adding features to meet more military requirements, including testing on common military unmanned and manned airborne platforms. Investigate the potential for transitioning portions of the technology to existing programs of record

REFERENCES:

  • Mark A. McHenry, Peter A. Tenhula, Dan McCloskey, Dennis A. Roberson, and Cynthia S. Hood. 2006. Chicago spectrum occupancy measurements & analysis and a long-term studies proposal. In Proceedings of the first international workshop on Technology and policy for accessing spectrum (TAPAS '06). ACM, N
  • SiXing Yin; Dawei Chen; Qian Zhang; Mingyan Liu; ShuFang Li, "Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study," Mobile Computing, IEEE Transactions on, vol.11, no.6, pp.1033,1046, June 2012.
  • da Silva, C.R.C.; Choi, B.; Kyouwoong Kim, "Distributed Spectrum Sensing for Cognitive Radio Systems," Information Theory and Applications Workshop, 2007, pp.120,123, Jan. 29 2007-Feb. 2 2007.

KEYWORDS: communications, sensors, electromagnetic spectrum, jamming, electronic warfare, signals intelligence

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