PERSEID

Decision-support tools for ISR collection management

Perceptual Sensing and Information Displays

The US Air Force is exploring how to improve the command and control (C2) of intelligence, surveillance, and reconnaissance (ISR) capabilities for air operations. Collection managers, who plan and execute ISR missions in Air Operations Centers (AOCs), must consider a wide range of information before making decisions. For example, when receiving requests for ISR, they must consider which assets are available, their capabilities, their suitability to the request, operating constraints (such as the priority of the request and whether the asset can arrive in time), and aspects of the environment (such as threats and weather). With so many options to choose from, collection managers must understand the tradeoffs to make the best decision in a timely manner. To improve this decision-making process and reduce the manual labor when planning and retasking assets, the Air Force is seeking and evaluating new technologies.

Demo image from Charles River Analytics project PERSEID.

The US Air Force is seeking new technologies to improve the decision-making process in air operations

COMPASS Overview

The Need

Current US Navy forecasting systems and mission planning tools rely exclusively on short-term forecasts or long-term statistical climate products to inform operational plans. Substituting short-term forecasts and statistical climate data with long-range (up to a year) forecasts can improve mission readiness and effectiveness, while ensuring safety and reducing cost, labor, and resource requirements.

As an example, when the MV Cape Ray was tasked with the destruction of Syria’s chemical weapons in 2014, the probability of extreme conditions (such as high wind speed) and the associated extreme sea state (high wave height) had to be factored in to accurately schedule the timing and location of the destruction.

The Solution

Charles River Analytics and our partners, the University of Miami and Clear Science, Inc., used machine learning to create COMPASS, which forecasts the probability that conditions will differ from long-term climatological averages or mission-specific thresholds.

The Benefit

Planners save time by interpreting a unified, single forecast that leverages the strength of multiple forecasts.

Technical Expertise

Perceptual Sensing and Information Displays

The US Air Force is exploring how to improve the command and control (C2) of intelligence, surveillance, and reconnaissance (ISR) capabilities for air operations. Collection managers, who plan and execute ISR missions in Air Operations Centers (AOCs), must consider a wide range of information before making decisions. For example, when receiving requests for ISR, they must consider which assets are available, their capabilities, their suitability to the request, operating constraints (such as the priority of the request and whether the asset can arrive in time), and aspects of the environment (such as threats and weather). With so many options to choose from, collection managers must understand the tradeoffs to make the best decision in a timely manner. To improve this decision-making process and reduce the manual labor when planning and retasking assets, the Air Force is seeking and evaluating new technologies.

Demo image from Charles River Analytics project PERSEID.

The US Air Force is seeking new technologies to improve the decision-making process in air operations

COMPASS Overview

The Need

Current US Navy forecasting systems and mission planning tools rely exclusively on short-term forecasts or long-term statistical climate products to inform operational plans. Substituting short-term forecasts and statistical climate data with long-range (up to a year) forecasts can improve mission readiness and effectiveness, while ensuring safety and reducing cost, labor, and resource requirements.

As an example, when the MV Cape Ray was tasked with the destruction of Syria’s chemical weapons in 2014, the probability of extreme conditions (such as high wind speed) and the associated extreme sea state (high wave height) had to be factored in to accurately schedule the timing and location of the destruction.

The Solution

Charles River Analytics and our partners, the University of Miami and Clear Science, Inc., used machine learning to create COMPASS, which forecasts the probability that conditions will differ from long-term climatological averages or mission-specific thresholds.

The Benefit

Planners save time by interpreting a unified, single forecast that leverages the strength of multiple forecasts.

Technical Expertise

The Charles River Analytics Solution

Charles River Analytics developed Perseid as a major component of the Air Force Lifecycle Management Center (AFLCMC) C2 Constellation’s Deliberate and Dynamic ISR Management (D2ISRM) initiative. Perseid provides decision-support tools for ISR collection management. These tools provide automated support for the enormous amount of manual data gathering and complex reasoning that collection managers must perform during planning and execution of ISR operations. During planning, Perseid allocates available assets to meet ISR requirements, generating multiple collection plan options. Perseid then helps the collection manager compare each option’s strengths and weaknesses before making a decision. During execution, Perseid provides a dynamic ISR synchronization matrix (ISR missions plotted on a timeline) to improve real-time situational awareness. Perseid also supports managing incoming requests for ISR by recommending retasking options. Each option is generated by automatically performing common manual calculations, such as time-to-target and intelligence gain/loss assessment. Perseid applies techniques from the fields of optimization and information visualization to present information in a way that helps collection managers rapidly make the most appropriate decision. As part of the D2ISRM initiative, The Perseid application was designed to work with the emerging AOC 10.2 modernization effort to minimize transition and sustainment costs as air operations evolve.

The US Air Force conducted an operational demonstration of D2ISRM captured in a video (below) summarizing the initiative. Representatives from the Air Force, MITRE, Charles River Analytics, and PatchPlus Consulting evaluated D2ISRM using operators from the 102nd Intelligence Wing, Air National Guard (ANG) in Bedford, MA, in April

D2ISRM presented at an operational demo

The Benefit

Perseid generates and presents options so collection managers can quickly make informed decisions. It reduces manual labor and dramatically expedites planning and retasking timelines; for example, Perseid reduced the time required for ISR operation planning from twenty hours to one hour. Perseid also improves situational awareness with a dynamic ISR synchronization matrix, which provides a current view of ISR operations with drill-down details. Perseid also supports ad hoc request management during execution by recommending retasking options (as seen in the figures below), which was shown to reduce processing timelines by a factor of 15. US Air Force officials noted how Perseid makes decision making easier and faster by recommending ISR platform tasking and retasking based on mission needs. In short, Perseid has the potential for improving the efficient and effective management of ISR assets.

Simulated image from Charles River Analytics project PERSEID.

Perseid displays multiple options and their tradeoffs in this tabular view

Simulated image from Charles River Analytics project PERSEID.

Perseid displays retasking recommendations to collection managers

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