Small Unmanned Aerial System for Surveying the Electromagnetic Spectrum

Small Unmanned Aerial System for Surveying the Electromagnetic Spectrum is sponsored by U.S. Department of Defense (Navy SBIR). This opportunity supports mission-aligned projects and measurable outcomes.

Small Unmanned Aerial System for Surveying the Electromagnetic Spectrum – Army SBIR|STTR Program Sensors, Army STTR, Phase I Small Unmanned Aerial System for Surveying the Electromagnetic Spectrum Application Due Date: 06/14/2023 Develop a UAS mountable sensor and transmit package that will provide a standalone low-cost survey, including geolocation, of the electromagnetic spectrum without the need for corporate support.

Many military and civilian applications require rapid survey of the electromagnetic spectrum for identification and the geolocation of electromagnetic emitters. A UAS provides an ideal platform for rapid surveys in possibly hazardous environments.

For example, in a natural disaster Emergency Management Services (EMS) require a rapid means of surveying the electromagnetic spectrum that will identify cell phone signals and locate the sources of those signals. The small tactical military unit has a similar need.

The technical challenges are developing a low weight sensor that will detect signals, provide geolocation from a small platform, and in real time relay the geolocation information back to decision makers. In the operational scenarios envisioned there cannot be the expectation of external technical support that would aid in the identification and classification of signals.

In addition, the form factor of the UAS should be one that enables a single person to carry and deploy, e.g., a quadcopter drone. With the recent development of lightweight, high fidelity RF components through advanced manufacturing techniques and advanced genetic algorithm design provide a new technology to enable the precision, range and SWAP needed for electromagnetic spectrum surveying in battlefield environments.

As an example, application specific electrically small antennas can be manufactured with minimal time, cost and weight. In addition, RF shielding for high-dynamic range measurements can be enabled through light-weight artificial materials acting as shields and directors, separating the electrically noisy components of a UAS from sensitive RF electronics.

Traditionally, communication signals have been identified through correlation of integrated emissions over a period of time. Civilian and military communications have evolved so that the frequencies use short duration pulsed communications and each emission at subsequent intervals can be centered at different frequencies. Technology is required to efficiently capture the presence of signals rather than the content of the actual signals.

Thus, it is more important to know that there is a signal and locate the source of the signal than to know details about the signal. Details such as operating frequency and modulation characteristics are not as important but would of course be of interest.

Geolocation is also important and possible solutions include using multiple UAS platforms, using synthetic aperture techniques, time of arrival, or possibly even signal strength determinations as the UAS flies in a formation. This topic shall be manufactured and/or assembled within the continental United States.

Develop a system design for a Class I or Class II UAS platform or platforms to map electromagnetic signal emitters including signal type and geolocation. The system should meet threshold values of a payload capacity of up to 10lbs and a minimum operational time of 15 minutes with a minimum observational range of 1 km and an objective payload weight of 5 lbs, operation time of 30 minutes, and observational range of 5km.

This should include a spectrum sensing algorithm for use on a UAS and a corresponding system hardware architecture. The objective for spectral sensing should be between 3MHz-6 GHz, able to sense RF power below -90 dBm and produce an accuracy of < 100 meter of signal emitter location. Design and fabricate a UAS electromagnetic sensing system including the algorithms developed in Phase I.

The system sensitivity will be improved to below -100dBm. The design of RF shielding and directionality for signal enhancement through custom antenna design and shielding will be demonstrated. The system should then be integrated with a UAS platform that meets or exceeds PHI standards with an improved flight time of no less than 30 minutes and range > 10km supporting maximum payload.

Data can be stored locally for retrieval upon return, however the ability to transmit data concurrently with spectrum and location mapping is desired. The UAS should be launchable from a single person. The sensing system should be able to: identify signal emitters by frequency and power, sense RF power below -100 dBm, and provide geolocation with <25m resolution.

The UAS platform demonstrated in Phase II will be developed for specific mission targets in collaboration with Army needs. It is expected that the payload capacity should increase to >15lbs, range should be increased to > 50 km with a flight time > 60 minutes and multiple sensing frequency bands can be concurrently sensed. The UAS system should be able to sense RF power below -100 dBm and geolocate with < 10 m resolution.

Please refer to the 23. B BAA for more information. Proposals must be submitted via the DoD Submission site at https://www.

dodsbirsttr. mil/submissions/login Martian, A. Real-time spectrum sensing using software defined radio platforms.

Telecommun Syst 64, 749–761 (2017). https://doi. org/10.

1007/s11235-016-0205-z Zhao, Xiaoyue & Pu, Fangling & Wang, Hangzhi & Chen, Hongyu & Xu, Zhaozhuo. (2019). Detection, Tracking, and Geolocation of Moving Vehicle from UAV Using Monocular Camera.

IEEE Access. PP. 1-1.

10. 1109/ACCESS. 2019.

2929760. Develop a UAS mountable sensor and transmit package that will provide a standalone low-cost survey, including geolocation, of the electromagnetic spectrum without the need for corporate support. Many military and civilian applications require rapid survey of the electromagnetic spectrum for identification and the geolocation of electromagnetic emitters.

A UAS provides an ideal platform for rapid surveys in possibly hazardous environments. For example, in a natural disaster Emergency Management Services (EMS) require a rapid means of surveying the electromagnetic spectrum that will identify cell phone signals and locate the sources of those signals. The small tactical military unit has a similar need.

The technical challenges are developing a low weight sensor that will detect signals, provide geolocation from a small platform, and in real time relay the geolocation information back to decision makers. In the operational scenarios envisioned there cannot be the expectation of external technical support that would aid in the identification and classification of signals.

In addition, the form factor of the UAS should be one that enables a single person to carry and deploy, e.g., a quadcopter drone. With the recent development of lightweight, high fidelity RF components through advanced manufacturing techniques and advanced genetic algorithm design provide a new technology to enable the precision, range and SWAP needed for electromagnetic spectrum surveying in battlefield environments.

As an example, application specific electrically small antennas can be manufactured with minimal time, cost and weight. In addition, RF shielding for high-dynamic range measurements can be enabled through light-weight artificial materials acting as shields and directors, separating the electrically noisy components of a UAS from sensitive RF electronics.

Traditionally, communication signals have been identified through correlation of integrated emissions over a period of time. Civilian and military communications have evolved so that the frequencies use short duration pulsed communications and each emission at subsequent intervals can be centered at different frequencies. Technology is required to efficiently capture the presence of signals rather than the content of the actual signals.

Thus, it is more important to know that there is a signal and locate the source of the signal than to know details about the signal. Details such as operating frequency and modulation characteristics are not as important but would of course be of interest.

Geolocation is also important and possible solutions include using multiple UAS platforms, using synthetic aperture techniques, time of arrival, or possibly even signal strength determinations as the UAS flies in a formation. This topic shall be manufactured and/or assembled within the continental United States.

Develop a system design for a Class I or Class II UAS platform or platforms to map electromagnetic signal emitters including signal type and geolocation. The system should meet threshold values of a payload capacity of up to 10lbs and a minimum operational time of 15 minutes with a minimum observational range of 1 km and an objective payload weight of 5 lbs, operation time of 30 minutes, and observational range of 5km.

This should include a spectrum sensing algorithm for use on a UAS and a corresponding system hardware architecture. The objective for spectral sensing should be between 3MHz-6 GHz, able to sense RF power below -90 dBm and produce an accuracy of < 100 meter of signal emitter location. Design and fabricate a UAS electromagnetic sensing system including the algorithms developed in Phase I.

The system sensitivity will be improved to below -100dBm. The design of RF shielding and directionality for signal enhancement through custom antenna design and shielding will be demonstrated. The system should then be integrated with a UAS platform that meets or exceeds PHI standards with an improved flight time of no less than 30 minutes and range > 10km supporting maximum payload.

Data can be stored locally for retrieval upon return, however the ability to transmit data concurrently with spectrum and location mapping is desired. The UAS should be launchable from a single person. The sensing system should be able to: identify signal emitters by frequency and power, sense RF power below -100 dBm, and provide geolocation with <25m resolution.

The UAS platform demonstrated in Phase II will be developed for specific mission targets in collaboration with Army needs. It is expected that the payload capacity should increase to >15lbs, range should be increased to > 50 km with a flight time > 60 minutes and multiple sensing frequency bands can be concurrently sensed. The UAS system should be able to sense RF power below -100 dBm and geolocate with < 10 m resolution.

Please refer to the 23. B BAA for more information. Proposals must be submitted via the DoD Submission site at https://www.

dodsbirsttr. mil/submissions/login Martian, A. Real-time spectrum sensing using software defined radio platforms.

Telecommun Syst 64, 749–761 (2017). https://doi. org/10.

1007/s11235-016-0205-z Zhao, Xiaoyue & Pu, Fangling & Wang, Hangzhi & Chen, Hongyu & Xu, Zhaozhuo. (2019). Detection, Tracking, and Geolocation of Moving Vehicle from UAV Using Monocular Camera.

IEEE Access. PP. 1-1.

10. 1109/ACCESS. 2019.

2929760. Assistant Secretary of the Army for Acquisition, Logistics, and Technology ASA(ALT) releases contract opportunities on an ad-hoc basis to meet Army research and development needs. Army Futures Command (AFC) releases topics during three specific solicitation periods throughout the fiscal year to address the Army’s current and anticipated war-fighting technology needs.

Army STTR follows AFC’s topic release schedule but partners with a university, federally funded research and development center, or a qualified non-profit research institution as part of their contract. Is the opportunity to establish the scientific, technical, commercial merit and feasibility of your proposed innovation. Is focused on the development, demonstration and delivery of your innovation from Phase I.

Represents the commercialization phase of the program in which the company can market their products or services developed in Phase II, either to the government or in the commercial sector. Allows small businesses to submit to Direct to Phase II applications if they performed the Phase I research through other funding sources. Provides funding to projects that require additional funding during their open Phase II contract.

A Phase II Awardee may receive one additional, sequential Phase II award to continue the work of an initial Phase II award. The sequential Phase II award has the same guideline amounts and limits as an initial Phase II award.

Artificial Intelligence/Machine Learning (supply chain management, logistics coordination, target identifications and simulation) Advanced Materials and Manufacturing (additive manufacturing) Autonomy (unmanned systems, drones, ground vehicle capabilities) Chemical and Biological (detection, defense) Cyber (biometric authentication, secure communications) Electronics (microelectronics, Very-Large-Scale Integration (VLSI)) Electronic Warfare (jamming, spoofing) Human Performance (wearables) Immersive (augmented reality, virtual reality, mixed reality) Network Technologies (antennas, radio frequency, communications systems) Position, Navigation, and Timing (GPS) Power (batteries, generators) Software Modernization (high performance computing, data management and visualization) Sensors (infrared sensing) Weapons Systems (hypersonics, munitions and projectiles, directed energy)