Privacy Policy
| Terms of Use
Use of U.S. DoD visual information does not imply or constitute DoD endorsement.
Learn more by selecting a product below:
Artificial Intelligence /
Machine Learning
BEFORE YOU BEGIN:
Please use this template as a reference to begin. In an effort to ensure all of our CFT experiences look similar, please keep the L3Harris logo in the same place and keep the font sizes for headlines and body copy consistent with what is provided below. Other than that you're free to modify and be as creative as possible!
Geospatial
Long Range Standoff
Tactical Edge Processing
TOP COVER
PED
JOINT ASSET
LRPF
ARES
JOINT CLOSE AIR SUPPORT
AIR LAUNCHED EFFECTS
NCCT
TITAN
TLS EAB
TLS EAB
TLS BCT
Labels On/Off
Tactical edge processing conducts battle damage assesment and nominates next target to include soldier lethality at the edge to identify and engage targets.
Kinetic and non-kinetic effects are launched against target.
Joint close air support receives tip & cue, positively identifies target.
TLS EAB responds with electronic attack/electronic warfare to disrupt targeting.
TITAN receives information and combines multiple sources of data. Data Analytics to Identify and Correlate Events (DICE) applies artificial intelligence & sense-making to shorten kill chain.
TLS EAB detects targeting details and forthcoming fire command.
Geospatial data from satellite assets classify and tighten target location.
Network centric collaborative targeting (NCCT) enables machine-to-machine collaboration & fusion. The information is sent to command and control networks.
Sherlock’s artificial intelligence gathers the data and applies machine learning to prioritize signals and provide tip & cue notifications in real-time.
Joint assets & ARES detect, identify & locate high value target: Adversary long-range fires targeting radar.
Net-Centric Autonomy and Resource Management (NCRM)
Step through scenario
Data analytics to Identify and Correlate Events (DICE)
Network Centric Collaborative Targeting (NCCT)
SHERLOCK
Step through scenario
Network Centric Collaborative Targeting (NCCT)
NCCT features automated machine-to-machine multi-intelligence sensor collection, cross cueing, and fusion of high value targets with integration across joint tactical and national assets. NCCT increases geolocation accuracy and decreases timelines to precision geolocations with confirmed Combat ID. The technology automates ISR processes to Decide, Detect, Deliver, and Assess effects within deep-sensing multi-domain environments.
Sherlock’s artificial intelligence/machine learning technologies increase mission effectiveness by delivering real-time insights from modern collection systems that emit structured and unstructured data. Its real-time data capabilities improve understanding of multiple data sources to aid the warfighter’s decision-making in multi-intelligence and multi-domain operations.
SHERLOCK
Artificial intelligence and machine learning (AI/ML) augment multi-domain operations by supporting automated sensor-to-shooter workflows. The integration of traditional and non-traditional intelligence and ISR capabilities increases electronic situational awareness and situational understanding (SA/SU) from Army and Joint sensing capabilities. DICE also supports tactical integration into the Army Electronic Warfare Planning and Management Tool (EWPMT) and provides automatic tip/cue to EWPMT and Long-Range Precision Fires.
Data analytics to Identify and Correlate Events (DICE)
Builds on Network Centric Collaborative Targeting with enhanced, impromptu teaming capabilities and tactical edge autonomy to extend the tactical and operational reach and increase the lethality of manned and unmanned assets. Supports autonomous manned/unmanned teaming and hierarchical control framework for Air Launched Effects. UAS self-organize and self-orient to perform mission ISR tasks and deliver kinetic and non-kinetic, lethal and non-lethal mission effects against multiple threats in non-permissive environments within the competition/conflict phases of multi-domain operations.
Net-Centric Autonomy and Resource Management (NCRM)
Step through scenario
ARIES-25 Long-Standoff EO/IR
ARES Electronic Warfare System
Sherlock
Network Centric Collaborative Targeting
Synthetic Labeled Data
IntelliEarth™ Integrator
Intellimatics
ENVI Deep Learning
Data Analytics
Salient Objection Detection
Particle Filter Tracker
Air-to-Air Detection
Net-Centric Autonomy
Our air-to-air detection and tracking solutions combine the best of advanced focal plane technology and ultra wide-angle lenses and packaging, with real time image processing from our missile defense experience. The integrated open systems architecture solution creates an ultra wide situational awareness Distributed Aperture System for manned and unmanned systems with features one would normally only expect to find a scanning infrared search and track system.
Air-to-Air Detection and Tracking
Working beyond the limitations of the Extended Kalman Filter (EKF), our particle filter tracker provides the ability to track multi-modal objects, i.e., troop carriers loading and unloading, port movement scenarios, and large crowds. Our technology supports multi-modal targets and tracks passing and overlapped objects. It works with several non-linear scenarios where KF and EKF trackers would fail.
Particle Filter Tracker
Salient Object Detection enhances a mission system’s ability to detect objects in a video stream without prior knowledge of the object’s existence.
Our system is based on a machine learning algorithm trained to use an assortment of image processing techniques, offering the operator the benefit of multiple algorithms for real-time detection of relevant objects in diverse situations.
Salient Object Detection
Knowledge and experience allow humans to anticipate what we expect to happen in the future. A rigorous computer program can do the same thing – better in some regards. Intellimatics provides near real-time intelligence that can automatically detect and track changes using time-based processing analogous to the real world.
More info: Download PDF
Intellimatics
The intelligence community (IC) is challenged with applying emerging artificial intelligence/machine learning (AI/ML) technologies to their datasets at scale. L3Harris’ IntelliEarth Integrator is designed specifically to meet Department of Defense and IC needs to deploy geospatial intelligence (GEOINT) AI/ML capabilities to the warfighter.
IntelliEarth™ Integrator
The U.S. intelligence community is drowning in available sensor data that may hold critical information to enhance missions. L3Harris is automating synthetic training data generation to streamline the time and cost of collecting training data for deep-learning applications. The technology requires little or no real training images, deploys new algorithms more rapidly, enables faster integration of new objects of interest and increases mission performance.
More info: Download Sellsheet
Synthetic Labeled Data for Overhead Automatic Target Recognition
The U.S. Army ARES aircraft is a technology demonstrator for the Army’s High Accuracy Detection and Exploitation System, or HADES program, capable of integrating capabilities from the Army’s existing ISR fleet with capacity to add payloads, sensors and increase standoff ranges. It can fly at mission altitudes above 40,000 feet for as long as 14 hours and can activate Long Range Precision Fires to counter long-range threats.
Airborne Reconnaissance and Electronic Warfare System (ARES)
ARIES-25 is a long standoff sensor system for demanding missions. It features six simultaneous cameras and advanced image processing that let you auto-detect and auto-track multiple targets simultaneously. The INS system provide sub-pixel, frame-to-frame stabilization and precision pointing, and static or DHCP network-enabled automatic configuration supports TCP/IP for command and control and video streaming per MISB standard, supporting multi-cast and UDP. Optional data recording systems enable the use of either raw or streamed video for post-mission analysis.
ARIES-25 Proven Long Rang Long Standoff EO/IR
L3Harris has developed commercial off-the-shelf deep learning technology that is specifically designed to work with remotely sensed imagery to solve geospatial problems. The ENVI Deep Learning module removes the barriers to performing deep learning with geospatial data and is currently being used to solve problems in agriculture, utilities, transportation, defense and other industries.
More info: Download PDF
ENVI Deep Learning
Privacy Policy
| Terms of Use
Use of U.S. DoD visual information does not imply or constitute DoD endorsement.
ARIES-25 Long-Standoff EO/IR
ARES Electronic Warfare System
Sherlock
Network Centric Collaborative Targeting
Synthetic Labeled Data
IntelliEarth™ Integrator
Intellimatics
ENVI Deep Learning
Data Analytics
Salient Objection Detection
Particle Filter Tracker
Air-to-Air Detection
Net-Centric Autonomy
Learn more by selecting a product below:
Builds on Network Centric Collaborative Targeting with enhanced, impromptu teaming capabilities and tactical edge autonomy to extend the tactical and operational reach and increase the lethality of manned and unmanned assets. Supports autonomous manned/unmanned teaming and hierarchical control framework for Air Launched Effects. UAS self-organize and self-orient to perform mission ISR tasks and deliver kinetic and non-kinetic, lethal and non-lethal mission effects against multiple threats in non-permissive environments within the competition/conflict phases of multi-domain operations.
Net-Centric Autonomy and Resource Management (NCRM)
Our air-to-air detection and tracking solutions combine the best of advanced focal plane technology and ultra wide-angle lenses and packaging, with real time image processing from our missile defense experience. The integrated open systems architecture solution creates an ultra wide situational awareness Distributed Aperture System for manned and unmanned systems with features one would normally only expect to find a scanning infrared search and track system.
Air-to-Air Detection and Tracking
Working beyond the limitations of the Extended Kalman Filter (EKF), our particle filter tracker provides the ability to track multi-modal objects, i.e., troop carriers loading and unloading, port movement scenarios, and large crowds. Our technology supports multi-modal targets and tracks passing and overlapped objects. It works with several non-linear scenarios where KF and EKF trackers would fail.
Particle Filter Tracker
Salient Object Detection enhances a mission system’s ability to detect objects in a video stream without prior knowledge of the object’s existence.
Our system is based on a machine learning algorithm trained to use an assortment of image processing techniques, offering the operator the benefit of multiple algorithms for real-time detection of relevant objects in diverse situations.
Salient Object Detection
Artificial intelligence and machine learning (AI/ML) augment multi-domain operations by supporting automated sensor-to-shooter workflows. The integration of traditional and non-traditional intelligence and ISR capabilities increases electronic situational awareness and situational understanding (SA/SU) from Army and Joint sensing capabilities. DICE also supports tactical integration into the Army Electronic Warfare Planning and Management Tool (EWPMT) and provides automatic tip/cue to EWPMT and Long-Range Precision Fires.
Data Analytics to Identify and Correlate Events (DICE)
L3Harris has developed commercial off-the-shelf deep learning technology that is specifically designed to work with remotely sensed imagery to solve geospatial problems. The ENVI Deep Learning module removes the barriers to performing deep learning with geospatial data and is currently being used to solve problems in agriculture, utilities, transportation, defense and other industries.
More info: Download PDF
ENVI Deep Learning
The intelligence community (IC) is challenged with applying emerging artificial intelligence/machine learning (AI/ML) technologies to their datasets at scale. L3Harris’ IntelliEarth Integrator is designed specifically to meet Department of Defense and IC needs to deploy geospatial intelligence (GEOINT) AI/ML capabilities to the warfighter.
IntelliEarth™ Integrator
The U.S. intelligence community is drowning in available sensor data that may hold critical information to enhance missions. L3Harris is automating synthetic training data generation to streamline the time and cost of collecting training data for deep-learning applications. The technology requires little or no real training images, deploys new algorithms more rapidly, enables faster integration of new objects of interest and increases mission performance.
More info: Download Sellsheet
Synthetic Labeled Data for Overhead Automatic Target Recognition
NCCT features automated machine-to-machine multi-intelligence sensor collection, cross cueing, and fusion of high value targets with integration across joint tactical and national assets. NCCT increases geolocation accuracy and decreases timelines to precision geolocations with confirmed Combat ID. The technology automates ISR processes to Decide, Detect, Deliver, and Assess effects within deep-sensing multi-domain environments.
Network Centric Collaborative Targeting (NCCT)
Sherlock’s artificial intelligence/machine learning technologies increase mission effectiveness by delivering real-time insights from modern collection systems that emit structured and unstructured data. Its real-time data capabilities improve understanding of multiple data sources to aid the warfighter’s decision-making in multi-intelligence and multi-domain operations.
SHERLOCK
The U.S. Army ARES aircraft is a technology demonstrator for the Army’s High Accuracy Detection and Exploitation System, or HADES program, capable of integrating capabilities from the Army’s existing ISR fleet with capacity to add payloads, sensors and increase standoff ranges. It can fly at mission altitudes above 40,000 feet for as long as 14 hours and can activate Long Range Precision Fires to counter long-range threats.
Airborne Reconnaissance and Electronic Warfare System (ARES)
ARIES-25 is a long standoff sensor system for demanding missions. It features six simultaneous cameras and advanced image processing that let you auto-detect and auto-track multiple targets simultaneously. The INS system provide sub-pixel, frame-to-frame stabilization and precision pointing, and static or DHCP network-enabled automatic configuration supports TCP/IP for command and control and video streaming per MISB standard, supporting multi-cast and UDP. Optional data recording systems enable the use of either raw or streamed video for post-mission analysis.
ARIES-25 Proven Long Rang Long Standoff EO/IR
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Return to List
Scroll for more
Artificial Intelligence /
Machine Learning
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Scroll for more
Artificial intelligence and machine learning (AI/ML) augment multi-domain operations by supporting automated sensor-to-shooter workflows. The integration of traditional and non-traditional intelligence and ISR capabilities increases electronic situational awareness and situational understanding (SA/SU) from Army and Joint sensing capabilities. DICE also supports tactical integration into the Army Electronic Warfare Planning and Management Tool (EWPMT) and provides automatic tip/cue to EWPMT and Long-Range Precision Fires.
Data Analytics to Identify and Correlate Events (DICE)
Return to List
Scroll for more
Return to List
Scroll for more
Intellimatics
Knowledge and experience allow humans to anticipate what we expect to happen in the future. A rigorous computer program can do the same thing – better in some regards. Intellimatics provides near real-time intelligence that can automatically detect and track changes using time-based processing analogous to the real world.
More info: Download PDF
Return to List
Scroll for more