Accession Number:

ADA280779

Title:

Quantifying the Value of Reconnaissance Using Lanchesterian Type Equations

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

• Johnson, Michael J.

Report Date:

1994-03-01

Pagination or Media Count:

81.0

Abstract:

This paper presents a method to quantify the value of reconnaissance for both direct and indirect fire weapons for the defense-in-sector battle scenario. The Lanchester area fire model and the Helmbold equations were modified to allow the lethality of the defending blue force to be increased as they gained more combat intelligence about the attacking red force, thus modeling intelligence as a true combat multiplier. By adjustments made to parameters in the model, the lethality of blue direct and indirect fire weapons could be adjusted based on the quantity and quality of their intelligence assets. With information from a computer database, and the COMAN model, maximum likelihood attrition rate estimates were calculated for both red and blue forces for ten heavy defensive battles conducted at the Armys National Training Center. In each battle, the red force attrition rate was fitted to a curve which represented a percentage of blues full potential, represented here by the square law. Using this model in a combat simulation, and with some preliminary work with comparable systems, one could implement a change in blues intelligence assets and then provide a quantitative measure of the effect that this had on the outcome of a battle. Reconnaissance, Attrition, Lanchester, Helmbold, FTLM, NTC.

Descriptors:

• *TACTICAL RECONNAISSANCE
• *WAR GAMES
• *STRATEGIC INTELLIGENCE
• DATA BASES
• COMPUTERIZED SIMULATION
• COMBAT EFFECTIVENESS
• DECISION MAKING
• LETHALITY
• INDIRECT FIRE
• BATTLES
• PARAMETERS
• MAXIMUM LIKELIHOOD ESTIMATION
• SECURITY
• ATTRITION
• THESES

Subject Categories:

• Military Intelligence
• Military Operations, Strategy and Tactics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE