# A Virtual Reality Soldier Simulator with Body Area Networks for Team Training
###### Abstract  
Soldier-based simulators have been attracting increased attention recently, with the aim of making complex military tactics more effective, such that soldiers are able to respond rapidly and logically to battlespace situations and the commander's decisions in the battlefield. Moreover, body area networks (BANs) can be applied to collect the training data in order to provide greater access to soldiers' physical actions or postures as they occur in real routine training. Therefore, due to the limited physical space of training facilities, an efficient soldier-based training strategy is proposed that integrates a virtual reality (VR) simulation system with a BAN, which can capture body movements such as walking, running, shooting, and crouching in a virtual environment. The performance evaluation shows that the proposed VR simulation system is able to provide complete and substantial information throughout the training process, including detection, estimation, and monitoring capabilities. virtual reality; body area network; training simulator +
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To overcome the limitations of the real-time training system, the dismounted soldier training system (DSTS) was developed [18; 19; 20; 21]. In the DSTS, soldiers wear special training suits and HMDs, and stand on a rubber pad to create a virtual environment. However, the inertial sensors of training suits can only recognize simple human actions (e.g., standing and crouching). When soldiers would like to walk or run in the virtual environment, they have to control small joysticks and function keys on simulated rifles, which are not immersive for locomotion. Thus, in a training situation, soldiers will not be able to react quickly when suddenly encountering enemy fire. As a result, though the DSTS provides a multi-soldier training environment, it has weaknesses with respect to human action recognition. Therefore, in order to develop a training simulator that is capable of accurately capturing soldiers' postures and movements and is less expensive and more effective for team training, body area networks (BANs) represent an appropriate bridge for connecting physical and virtual environments [22; 23; 24; 25; 26], which contain inertial sensors like accelerometers, e-compasses and gyroscopes to capture human movement. Xsens Co. have been developing inertial BANs to track human movement for several years. Although the inertial BAN, called the MVN system, is able to capture human body motions wirelessly without using optical cameras, the 60 Hz system update rate is too slow to record fast-moving human motion. The latest Xsens MVN suit solved this problem, reaching a system update rate of 240 Hz. However, the MVN suit is relatively expensive in consumer markets. In addition, it is difficult to support more than four soldiers in a room with the MVN system, since the wireless sensor nodes may have unstable connections and high latency. On the other hand, since the Xsens MVN system is not an open-source system, the crucial algorithm of the inertial sensors does not adaptively allow the acquisition by and integration with the proposed real-time program. Moreover, the MVN system is only a motion-capture BAN and is not a fully functional training simulator with inertial BANs [26]. For the above-mentioned reasons, this paper proposes a multi-player training simulator that immerses infantry soldiers in the battlefield. The paper presents a technological solution for training infantry soldiers. Fully immersive simulation training provides an effective way of imitating real situations that are generally dangerous, avoiding putting trainees at risk. To achieve this, the paper proposes an immersive system that can immediately identify human actions. Training effectiveness in this simulator is highly remarkable in several respects:  
1.