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C4ISR Analytic Performance Evaluation Models

by Susan Parker and Henry Neimeier

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Overview

MITRE has developed the capability to quickly construct models that generate key insights into the relative contributions of C4ISR systems, weapons, and platforms to military mission effectiveness. The term "CAPE" stands for C4ISR Analytic Performance Evaluation and is used to describe this modeling methodology as well as the set of models which use a common approach in their construction and representation of various factors.

The CAPE models have filled a void in the C4ISR modeling community by providing a set of tools, useful for quick-look studies that provide necessary insights into key C4ISR parameters and interactions. This unique capability has led customers to seek MITRE assistance in answering complex system problems in a timely and efficient manner. As the need arises, new models are developed using the common modeling approach and added to the CAPE tool set.

 

CAPE Methodology

The CAPE methodology provides the capability to model the whole strike process analytically from environment generation to calculation of measures of effectiveness. This includes the sensor collection system, processing, exploitation, dissemination, and command and control process.

Probabilistic Environment

One of the unique features of CAPE models is that environments are described probabilistically to simplify scenario generation. The range of parameter values is specified with a probability distribution rather than a single point estimate. The analytic uncertainty analysis technique is used in place of stochastic discrete event simulation methods. Discrete event simulations require many simulation runs in order to get a statistically significant estimate of the mean for desired measures of effectiveness. Analytic uncertainly analysis calculates the entire measure-of-effectiveness distribution in a single step, this providing a probability density function for the measures being analyzed.

Sensor Collection

Different sensor collection architectures are compared in CAPE models. Collection parameters such as sensor locations or tracks, sensor detection sensitivity, coverage rate, and duty cycle are considered in the models. Additionally, the impact of weather, terrain and foliage masking, enemy concealment, cover, and deception are calculated. In some CAPE models, dynamic deployment of sensors, and attrition by enemy forces, are also modeled.

Processing, Exploitation, and Dissemination (PED)

Communication and information processing are often weak links in weapon system performance. CAPE dynamically calculates communication system loading and resulting delays. Human and computer processing loading in the PEDS process is calculated along with resulting delays. Distributed processing and split base concepts have been evaluated in some past CAPE analyses.

Weapon Systems

There is a strong interaction between intelligence, surveillance, and reconnaissance (ISR) capabilities and weapon system capabilities. The CAPE models have been used to demonstrate that excellent ISR without an adequate inventory of precision weapons does not improve performance. Similarly, the models have shown that large inventories of precision weapons and executing platforms, without timely ISR systems, have little value against time-sensitive targets. CAPE models these interactions by a dynamic optimal allocation of platform and weapons to targets.

Command and Control

One role of C2 is to select the appropriate strike platforms and weapons to attack targets. This allocation dynamically changes through the scenario as a function of battle phase, ISR system capability, remaining enemy targets, and remaining inventory of strike platforms and weapons. In some CAPE models, the optimal combination of weapon, platform, and target is calculated based on a user-selected value function. Target mobility, required weapon target location error, and platform execution time are considered in the allocation.

CAPE Measures of Effectiveness

Several measures of effectiveness (MOE) are calculated by the different CAPE models. These include: percent of imagery collected that is exploited, exploitation delay, sensor-to-shooter delay, proportion of original targets remaining, attrition of blue strike and sensor platforms, attrition of red land targets, dynamic red-blue force ratios, battle phase duration, targets at risk, and battle cost. The targets at risk MOE is calculated by comparing the sensor-to-shooter time distribution to the target mobility distribution. Targets at risk is the probability that a mobile target is within the acquisition envelope of the assigned weapon when it arrives at a sensed target location.

CAPE Models and their Application

The CAPE methodology has been applied to a wide variety of problems, and has been used successfully to support numerous customers.

• Deep CAPE looks at theater deep strike with Air Force planes and Army ATACMs missiles.
• Close CAPE concentrates on Army close battle in a division slice of a theater.
• Sea CAPE evaluates potential future threats and defenses of Navy task forces.
• Air CAPE focuses on the future surface to air missile threat. It is being used to guide information superiority exercise development and encode results in an easily extensible form.
• Geographic CAPE calculates dynamic battlespace awareness. It uses a cellular automatic technique to probabilistically move forces on a battlefield. Ground truth is dynamically compared to sensed truth and differences are scored.
• Dynamic CAPE performs optimal platform-weapon-target allocation. It is used to evaluate several alternative C4ISR architectures. Balanced C4ISR/weapon system expenditures can be calculated in these cases.
• PEDS CAPE models the performance of an imagery exploitation system as a function of collection quantity, number of imagery analysts and exploitation rates.

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For more information, please contact Susan Parker using the employee directory.

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