ROSEMARY_IARPA-RFI-24-05_C.pdf

UNCLASSIFIED

Opportunities for Observing and Sensing Atmospheric Electromagnetic Anomalies

Request for Information: Opportunities for Observing and Sensing Atmospheric Electromagnetic Anomalies

RFI Number: IARPA-RFI-24-05

Agency: Office of the Director of National Intelligence Office: Intelligence Advanced Research Projects Activity

IARPA-RFI-24-05

Synopsis:

Request for Information (RFI): Opportunities for Observing and Sensing Atmospheric Electromagnetic Anomalies

The Intelligence Advanced Research Projects Activity (IARPA) seeks information regarding innovative signal processing algorithms and sensing approaches used to characterize the D-region of the ionosphere (60–90 km).

Currently, the D-region is characterized by remote sensing of very low frequency (VLF) signals and comparing that propagation with modeling results.1-2,3 However, this approach is highly nonlinear and fits the definition of an ill-posed problem in that itis quite difficult to solve and does not yield a unique one-to-one correspondence between electron density profiles in the Earth-ionosphere waveguide and signals at the receiver(s). In the past decade, inversions of highly nonlinear, ill-posed problems have been successfully tackled with machine learning and artificial neural networks (ANNs).4-5,6,7 While significant progress has been made in signal processing,8-91011 the data used by these algorithms is obtained by sensors that are uncoordinated and loosely networked. Additionally, the uncoordinated environmental monitoring sensors used to collect data cannot provide real-time estimates of the D-region, needed to support high-accuracy detection, geolocation and classification solutions.

IARPA seeks to characterize and better understand the D-region and the interaction of this region of the ionosphere with electromagnetic (EM) anomalies caused by space weather events, lightning, manmade sources, etc.12,13 and whether the resulting D-region characterization can be used to identify, map, and track these EM anomalies. Current capabilities do not allow for the rapid parametrization of the D-region. Any methodology that could lead to this rapid parametrization is of interest as we seek to facilitate a domain awareness capability that currently does not exist.14

Background & Scope:

Low frequency radio waves, below 30 MHz,15 are useful for strategic communications due to their ability to propagate global distances and to reach underground facilities and submersibles.16,17 The radio frequencies (RF) within this part of the electromagnetic spectrum propagate between the Earth and the D-region of the ionosphere (60–90 km) forming a waveguide known as the Earth-ionosphere waveguide (EIWG). While the electrical properties of the Earth’s surface and Earth’s magnetic field are more or less stable and well-understood, the electrical and magnetic properties of the D-region of the ionosphere are not, due to electron density irregularities. These irregularities occur across latitude, longitude, and elevation, and are time-varying across the day and time of year.18 Furthermore, the D-region is highly reactive to EM anomalies caused by electron density irregularities as previously discussed. In order to improve domain awareness, specifically real-time identification and geolocation of manmade EM anomalies, it is essential to characterize the volatility of the D-region.

Electron density irregularities are frequently studied using signal processing techniques that uses data obtained from various largely uncoordinated ionosphere measurement systems, to include ground-, air-, & space-based sensors,19 ionosondes,20 Langmuir probes,21 and high frequency (HF) communication sensors.22 This methodology is useful in characterizing the upper regions of the ionosphere or local D-region irregularities, but are inadequate in characterizing the D-region across vast geographic regions containing propagation paths of interest.

Current signal processing techniques based on data from uncoordinated ground-based remote environmental monitoring sensors are not likely to meet the challenge of characterizing the D-region over propagation paths of interest, nor achieve the speed and accuracy needed to provide real-time domain awareness of manmade EM anomalies. Thus, IARPA invites white papers describing promising approach or methodology that could lead to the rapid parametrization of the D-region.

For IARPA to evaluate the promise of potential new approaches, it is necessary to consider the following:

a. existing or newly proposed signal processing techniques for characterizing the irregularities in the D-region;

b. existing or newly proposed technology for networked ground sensors;

c. sensor types including but not limited to 3 MHz and below;

d. pertinent physical phenomena including but not limited to electrostatic discharge, electric field perturbations, magnetic field perturbations, and/or radio wave emissions produced as EM anomalies interact with the surrounding regions of the ionosphere and the earth surface;

e. specialized sensor collection modes including but not limited to interferometry, polarimetry, and/or coincident collection with ground/air/space sensors;

f. novel detection techniques for low signal to noise EM anomalies;

g. probabilistic detection techniques for low signal to noise EM anomalies; and

h. capabilities that improve the resolution and cadence of data assimilation systems, providing for a more accurate characterization of the D-region at a desired observation time and over propagation paths of interest.

Responses can address any one or multiple of these considerations.

In response to submissions to this RFI, IARPA may organize an invitation-only workshop for the purpose of reviewing and discussing relevant current and future research. Should a workshop occur, participants may be asked to make formal presentations based on their RFI submissions or associated research. Written submissions and information discussed at a workshop may assist in the formulation of future U.S. Government research.

Preparation Instructions to Respondents:

IARPA requests that respondents submit ideas related to this topic for use by the Government in formulating a potential program. IARPA requests that submittals briefly and clearly describe the potential approach or concept, outline critical technical issues/obstacles, describe how the approach may address those issues/obstacles, and comment on the expected performance and robustness of the proposed approach. If appropriate, respondents may also choose to provide a non-proprietary rough order of magnitude (ROM) estimate regarding what such approaches might require in terms of funding and other resources for one or more years. This announcement contains all of the information required to submit a response. No additional forms, kits, or other materials are needed.

IARPA welcomes responses from all capable and qualified sources from within and outside of the U.S.

Because IARPA is interested in an integrated approach, responses from teams with complementary areas of expertise are encouraged.

Responses must meet the following formatting requirements:

• a one-page cover sheet that identifies the title, organization(s), respondent's technical and administrative points of contact - including names, addresses, phone and fax numbers, and email addresses of all co-authors, and clearly indicating its association with IARPA-RFI-24-05;

• a substantive, focused, one-half page executive summary;

• a description (limited to 5 pages in minimum 12-point Times New Roman font, appropriate for single-sided, single-spaced 8.5 by 11-inch paper, with 1-inch margins) of the technical challenges and suggested approach(es);

• a list of citations (any significant claims or reports of success must be accompanied by citations); and

• a single quad-chart depicting the (a) approach, (b) supportive illustrations, (c) key ideas, and (d) potential impact.

Submission Instructions to Respondents:

Responses to this RFI are due no later than 5:00 p.m., Eastern Time, Monday, 17 JUN 2024. All submissions must be electronically submitted to dni-iarpa-rfi-24-05@iarpa.gov as a PDF document. Inquiries to this RFI must be submitted to dni-iarpa-rfi-24- 05@iarpa.gov no later than 5:00 p.m., Eastern Time, Monday, 17 JUN 2024. Do not send questions with proprietary content. No telephone inquiries will be accepted.

Disclaimers and Important Notes:

This is an RFI issued solely for information and planning purposes and does not constitute a solicitation. Respondents are advised that IARPA is under no obligation to acknowledge receipt or provide feedback to respondents with respect to any information submitted under this RFI. Responses to this notice are not offers and cannot be accepted by the Government to form a binding contract. Respondents are solely responsible for all expenses associated with responding to this RFI. IARPA will not provide reimbursement for costs incurred in responding to this RFI. It is the respondent's responsibility to ensure that the submitted material has been approved for public release by the information owner. The Government does not intend to award a contract on the basis of this RFI or to otherwise pay for the information solicited, nor is the Government obligated to issue a solicitation based on responses received. No proprietary and no classified concepts or information shall be included in the submittal. However, should a respondent wish to submit classified concepts or information, prior coordination must be made via email to the aforementioned alias with your request to submit a classified response. Input on technical aspects of the responses may be solicited by IARPA from non-Government consultants/experts who are bound by appropriate non-disclosure requirements.

Contracting Office Address:

Office of the Director of National Intelligence, Intelligence Advanced Research Projects Activity Washington, District of Columbia 20511, United States

Primary Point of Contact:

Dr. Mickey Batson, Program Manager Intelligence Advanced Research Projects Activity

References 1 (U) S. A. Cummer, Lightning and ionospheric remote sensing using VLF/ELF radio atmospherics.

Stanford University, 1997.

2 (U) M. Gołkowski, S. Sarker, C. Renick, R. Moore, M. Cohen, A. Kułak,J. Młynarczyk, and J. Kubisz, “Ionospheric d region remote sensing using elf sferic group velocity,” Geophysical Research Letters, vol. 45, no. 23, pp. 12–739, 2018.

3 (U) J. C. McCormick, “D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling,” Ph.D. dissertation, Georgia Institute of Technology, 2019.

4 (U) C. Zhang, C. Frogner, M. Araya-Polo, and D. Hohl, “Machine-learning based automated fault detection in seismic traces,” in 76th EAGE Conference and Exhibition 2014, vol. 2014, no. 1. European Association of Geoscientists & Engineers, 2014, pp. 1–5.

5 (U) Y. Wu, Y. Lin, Z. Zhou, and A. Delorey, “Seismic-net: A deep densely connected neural network to detect seismic events,” arXiv preprint arXiv:1802.02241, 2018.

6 (U) M. Raissi, P. Perdikaris, and G. E. Karniadakis, “Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,” Journal of Computational physics, vol. 378, pp. 686–707, 2019.

7 (U) C. Jiang, D. Zhang, and S. Chen, “Lithology identification from well log curves via neural networks with additional geologic constraint,” Geophysics, vol. 86, no. 5, pp. IM85–IM100, 2021.

8 (U) J. C. McCormick, “D region tomography: A technique for ionospheric imaging using lightning-generated sferics and inverse modeling,” Ph.D. dissertation, Georgia Institute of Technology, 2019.

9 (U) N. Gross and M. Cohen, “Vlf remote sensing of the d region ionosphere using neural networks,” Journal of Geophysical Research: Space Physics, vol. 125, no. 1, p. e2019JA027135, 2020.

10 (U) D. K. Richardson and M. B. Cohen, “Seasonal variation of the d-region ionosphere: Very low frequency (vlf) and machine learning models,” Journal of Geophysical Research: Space Physics, vol.

126, no. 9, p.e2021JA029689, 2021.

11 (U) J. R. Wait, Characteristics of the Earth-ionosphere waveguide for VLF radio waves. US Department of Commerce, National Bureau of Standards, 1964, vol. 300.

12 (U) A. P. Mitra, Ionospheric effects of solar flares. Springer, 1974, vol. 46.

13 (U) R. Helliwell, J. Katsufrakis, and M. Trimpi, “Whistler-induced amplitude perturbation in vlf propagation,” Journal of Geophysical Research, vol. 78, no. 22, pp. 4679–4688, 1973.

14 (U) J. R. Wait, Characteristics of the Earth-ionosphere waveguide for VLF radio waves. US Department of Commerce, National Bureau of Standards, 1964, vol. 300.

15 (U) J. A. Holtet and E. Swanson, “Elf-vlf applications in navigation and communications,” in ELF-VLF

Radio Wave Propagation: Proceedings of the NATO Advanced Study Institute held at Sp˚atind, Norway, April 17–27, 1974. Springer, 1974, pp. 371–384.

16 (U) P. Morris, R. Gupta, R. Warren, and P. Creamer, “Omega navigation system course book. volume 1,2,” ANALYTIC SCIENCES CORP READING MA, Tech. Rep., 1994.

17 (U) J. Ferguson, “Ionospheric profiles for predicting nighttime vlf/lf propagation, determination of an effective (exponential) model for use in design and deployment of resources for communication and navigation,” NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA, Tech. Rep., 1980.

18 (U) M. A. Higginson-Rollins and M. B. Cohen, “Measuring the electron density roughness of the d-region ionosphere,” Journal of Geophysical Research: Space Physics, vol. 125, no. 10, p.

e2020JA028111, 2020.

19 (U) N. A. Zabotin and J. W. Wright. Ionospheric irregularity diagnostics from the phase structure functions of MF/HF radio echoes. Radio Science, 36(4):757-771, Jul 2001.

20 (U) M.T. Rietveld, J.W. Wright, N. Zabotin, and M.L.V. Pitteway. The Tromsø dynasonde. Polar Science, 2(1):55-71, Mar 2008.

21 (U) H. S. S. Sinha. Rocket-borne Langmuir probe for plasma density irregularities, page 77-90.

Terrapub, 2013.

22 (U) Biagio Forte, Chris Coleman, Susan Skone, Ingemar Haggstrom, Cathryn Mitchell, Federico Da Dalt, Tommaso Panicciari, Joe Kinrade, and Gary Bust. Identification of scintillation signatures on GPS signals originating from plasma structures detected with EISCAT incoherent scatter radar along the same line of sight. Journal of Geophysical Research: Space Physics, 122(1):916-931, Jan 2017.