Military researchers are urging industry to develop ionospheric computer models to improve HF radio propagation | Panda Anku

ARLINGTON, Va.— US military researchers are urging the industry to develop new ways to model the ionosphere in real time to help predict the propagation of radio frequency (RF) radio waves for improved communications and sensing.

Officials at the US Defense Advanced Research Projects Agency in Arlington, Virginia last week (HR001122S0028) issued a call for tenders for the Ouija TA-2 project to develop real-time modeling for assimilative ionospheric and HF radio propagation.

The ionosphere is the ionized portion of the Earth’s upper atmosphere, from about 30 miles to 600 miles above sea level, that is ionized by solar radiation. It affects radio propagation to distant locations on earth by reflecting RF signals.

HF radio uses signals at relatively long wavelengths, between 10 and 100 meters. HF radio bands lie between the commercial AM and FM broadcast bands and operate from 3 to 30 MHz. HF radio waves are characterized by their ability to propagate signals over long distances by bouncing signals off the ionosphere.

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RF radios are also notorious for static buildup from lightning storms and other radio frequency interference. The ionosphere is constantly changing and can affect HF radio signals from minute to minute and from season to season.

One goal of the Ouija TA-2 project is to develop near real-time assimilating ionospheric computer models that can mimic ionospheric perturbations on scales of 100 kilometers and below.

These models must assimilate ionospheric measurements taken with the scientific instrument packages to be flown in very low earth orbit (VLEO) on the Ouija TA-1 CubeSats, in addition to standard vertical and oblique sonar data. Science instrumentation on the Ouija spacecraft will include Langmuir probes and similar devices to measure electron density and other quantities of interest.

The aim is to predict the properties of the ionosphere in near real time with unprecedented resolution and accuracy, DARPA researchers say.

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The second objective is to develop high-fidelity RF radio propagation models to support the prediction of ground-to-VLEO radio wave propagation, which will be validated by in-orbit measurements performed by the Ouija spacecraft RF payload, which will carry test signals from cooperative terrestrial devices will receive transmitters.

Researchers expect industry to develop RF radio propagation models by combining ionospheric models using in-orbit measurements with an RF propagation prediction model that will provide highly accurate predictions of ground-to-space RF radio propagation.

The scientific payload will measure ionospheric properties in near real time using Langmuir probes, magnetometers and Global Navigation Satellite System (GNSS) instruments to estimate electron density profiles using radio occultation. The HF payload consists of an HF antenna and a receiver for receiving test signals from terrestrial transmitters.

One goal is the ability to predict the ionosphere using high-fidelity models updated at a rate of 10 seconds per update rather than minutes per update, which should be sufficient to predict HF radio propagation for ground-to-ground HF links to predict space.

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The nine-month first phase of the project will begin modeling before data is available from the Ouija VLEO satellites. Instead, sonar measurements are used from a terrestrial HF radio transmitter to low earth orbiting (LEO) satellites equipped with an HF receive payload.

The year-long second phase will assimilate data from a VLEO satellite and generate electron density distributions. The 16-month third phase will assimilate on-orbit data from six Ouija satellites. DARPA researchers say they expect to award multiple contracts.

Interested companies should upload unclassified proposals to the DARPA BAA website at https://baa.darpa.mil no later than September 23, 2022.

Email DARPA any questions or concerns at HR001122S0028@darpa.mil. More information is available online at https://sam.gov/opp/33f627f25a5d48a19f73539e0c73f307/view.

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