Injecting Realistic Human Models into the Optical Display of A Future Land Warrior System for Embedded Training Purposes

Abstract

Head Mounted Displays (HMDs) have traditionally been and are currently utilized in a variety of applications including training, entertainment, and military operations. Most applications of HMDs seek to provide the user with enriched information, that is, information beyond that of what a human can gather with only biological vision.

The Land Warrior is an operational system that utilizes a HMD. For Land Warrior, the HMD provides the Soldier better battle field situational understanding through text by communicating command and control information. Other Land Warrior battlefield tasks include target detection and recognition.

This paper evaluates the visual components of the current Ground Soldier System (GSS), Land Warrior HMD, analyzes embedded training requirements (specifically detection ranges for embedded virtual targets and human performance issues associated with HMDs), and proposes an optical model to overcome some of the limitations inherent to the current commercial version of the Land Warrior HMD and other commercially-available HMDs.

The design quality of the Land Warrior HMD has a direct impact on a soldier's performance in the field. The varying stringent environment in which LW operates provides HMD visual component design challenges, due to the correlation between the equipment style, information formatting, and use environment. Information formatting affects a Soldier's workload. The current LW HMD visual implementation contains information formatting limitations based on its ability to scale to other resolutions and size linearly.

By increasing the performance of the HMD of the Land Warrior System, the potential to improve readiness and survivability also increase. Forty-five thousand sets of Land Warrior equipment will be fielded between 2001 and 2014.

Keywords

Modeling & Simulation Military Applications Embedded Training Head-Mounted Display Optical Design Information Formatting

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