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Innovative and Intelligent Standoff Detection Algorithm



OBJECTIVE: Develop innovative and intelligent Standoff Detection Algorithms for remotely operated explosive hazard detection systems.

DESCRIPTION: The U.S. Army is looking to improve the detection capabilities for robotic explosive hazard detection systems.The existing system has demonstrated success leveraging existing algorithms from the handheld detector that it utilizes.However, due to the additional processing power on board the platform and ability to mount sensors to monitor the detector itself, there is potential to develop algorithms to enhance the signal coming from the detector(s).Without the critical size weight and power restrictions of a handheld device, the robotic platform has the ability to process additional data and integrate more inputs.There are opportunities to implement volumetric analysis, enhanced visualization, augmented reality, and machine learning or artificial intelligence to improve the detection capabilities (by learning from past experiences), intelligently integrate signals from multiple sensors (such as ground penetrating radar, pulsed induction, and electromagnetic induction, and relay of that information to the user.Advances in detection algorithms beyond the existing performance can improve the detection capability, increasing the survivability of the system and most importantly the warfighter.The end result of this effort will be mature algorithms that can undergo testing for detection performance and human factors.This effort will help advance the maturation of a solution to be able to rapidly field a capability.

PHASE I: Phase I will result in laboratory and field demonstrations of the prototype algorithm(s) to test the ability to meet requirements. Simulated hazards will be used to test the system. The primary objective of these tests will be to demonstrate the detection and processing speed as it relates to false vs true readings.The Phase I Option, if awarded, will develop the system specification based on results of the Phase I demo, which will be used to drive requirements for Phase II.

PHASE II: Phase II will fully mature the algorithms to a robustness required to demonstrate in a simulated operational environment, and integrated into the demonstration platform. Phase II will culminate with an operational demonstration at a government facility using a combination of simulated and actual hazards.

PHASE III: Phase III will consist of full qualification of the technology in the host system in preparation for transition to fielding.

KEYWORDS: hazard detection, mine detection, explosive detection, robotics, tele-operate, mine detector, hand held detector, UXO, metal detector, trip wire


Comparisons of Ring Resonator Relative Permittivity Measurements to Ground Penetrating Radar Data, Marie Fishel & Phillip Koehn, April 2014,; Electromagnetic Induction and Magnetic Sensor Fusion for Enhanced UXO Target Classification, Dr. H.H. Nelson, February 2004,; A hybrid full MAS and Combined MAS/TSA Algorithm for Electromagnetic Induction Sensing, F. Shubitidze, K. O’Neill, K. Sun, I. Shamatava, and K. D. Paulsen, MARCH 2004,; Multi-Source Fusion for Explosive Hazard Detection in Forward Looking Sensors, Derek Anderson, December 2017,

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