## 2 Introduction to Analytical Scenario  
The presented research on utilizing Augmented Reality (AR) technology and analytical products concentrates on developing specialized combat functionality, which directly supports battlespace data acquisition, processing, and distribution between friendly side assets (gaining decision superiority). This task is performed using handheld devices connected to secured tactical networks through the application of specialized network interfaces. Figures 1 and 2 present a test scenario that presents thereporting and recon aggregation capabilities of the mCOP toolkit. The presented figures document the combat scenario time snapshots reported and registered by separate reconnaissance elements, which during a mission are supplemented with detailed unit information [5,6]. Each recon report contains a marked enemy or unknown elements' estimated placements, any equipment recognized, and personnel. Using intelligence knowledge about an enemy unit's doctrinal composition, a system can recognize and determine unit templates (also considering different aggregation levels).  
To support the type of recon data reported in each mCOP application, mCOP is able to register an individual or group of equipment/vehicles, marking their warfare type or specific model or utilizing IoT-based sensors [5]. The fusion of such data is performed automatically in the tCOP [10] server and is further distributed to lower-level mCOP node applications. The fusion algorithm utilizes the reliability of the reporting source and the correlating data of individual military equipment and groups. Utilizing doctrinal patterns, the algorithms identify and recognize specific unit types and their affiliations based on the numbers and types of equipment supplemented with communications and command system parameters. The mCOP application contains an editable and configurable equipment database (internal), which can be updated and extended through server service or manual interactions. However, to fully utilize Tactical Augmented Reality View (TARV) battle space object annotations and evaluations (Figure 3), it is required that the operator provide equipment data as an outcome of the performed reconnaissance tasks.  
Figure 1: Initial combat situation projected on a 2D map view (map view in mCOP application). Initial report with grouped suspected elements (**a**). Updated combat situation demonstrating aggregated recon reports detailing reported enemy assets forming combat units (**b**).  
A database of military equipment is further used to determine the full composition of recognized units, formulating military unit potentials, which can be further used for tactical calculations utilizing [PERSON]'s model [2,11]. With detailed scenario data stored in its combat database, mCOP is capable of calculating the combat outcomes of the selected enemy and the friendly units in various dynamic tack configurations. This delivers to tactical commanders a powerful tool for current situation evaluation. The described situation is the basis for further studies and presentations on the implementation of battlespace evaluation algorithms. To demonstrate such capabilities, we will consider a scenario composed of Tables 1 and 2 elements (infantry battalion vs three enemy battalions).