Simulation Modeling of Armed Confrontation in Aerospace

Abstract. This paper examines the scope of the simulation modeling method to propose the general theoretical aspects and grounds of creating and applying simulation modeling of armed confrontation by troop/force groupings in aerospace.

In military science and the practice of troop/force command and control (C2) nowadays experts readily resort to simulation models. What acts as an armed confrontation modeling object in most cases is combat actions by troop/force groupings at various levels as a complex phenomenon developing in time and space. The employment of simulation models apparently enables the researcher to study and discover new regularities of armed struggle, verify and specify certain theoretical propositions (concepts), and work out and improve forms and methods of fighting in various situations.

Until recently it was no simple matter to develop and apply large-scale simulation models of combat actions by formations (troop/force groupings of the Aerospace Forces (ASF)) as an integral phenomenon owing to some objective and subjective reasons.

• First, there was no such service as the ASF of the RF Armed Forces. When the ASF were set up, the developed and adopted mathematical models at the AD Troops, Air Force, and Aerospace Forces reflected only those processes that were characteristic of the specific service (arm) of the RF AF.
• Second, formalizing processes occurring in aerospace was a complicated job, as was the mathematical formalization of the spatiotemporal functioning dynamics of surface (ground and water), aerodynamic, ballistic, and space assets.
• Third, there were no tactical, operational, and strategic bases of the mathematical formalization of combat actions in aerospace that would be comprehensive enough.

At the same time, the accumulated experience of developing, introducing, and employing mathematical models of complex systems functioning, and advanced techniques of simulation modeling helps substantiate the operationalstrategic and systemic-technical foundations of simulation modeling of combat actions by opposing groupings in aerospace.

The basics of combat actions simulation modeling are viewed as a sum of main provisions that constitute the source basis for the development and application of simulation models, given the specific features of actions by ASF military formations and adversary aerospace attack weapons (ASAW). Simulation modeling makes for creating a high-quality quantitative base of decisions to be taken, helps raise the efficiency and judgment assessment, ensures the forecasting of combat actions outcome in various situations, and helps simulate the functioning of existing and prospective types of weapons and military hardware guaranteeing highly accurate results.

Simulation models, in contrast to other methods of representing combat actions, rely on the principle of copying the processes modeled. Simulation models are based on making copies of combat actions preserving the logical makeup and ties between the constituents (elements). As compared to analytical modeling, the simulation variety makes for the following:

• a more detailed simulation of combat employment of the opposing sides’ forces and assets, ensuring a graphic representation of the results achieved;
• adjustment while modeling of the activity both by own and adversary troops/forces;
• visual observation of the opposing sides’ actions simulation and a more detailed assessment of numerous factors effect on the course and outcome of combat actions.

The development of simulation modeling methodology yielded two methods of formalizing system functioning.

The commonest is the method of constant increment or At method. According to this method, the modeled system’s state is reproduced at a fixed time interval, At, and events occur in the system during the At time whose value should be selected depending on the minimum duration of the modeled assets working cycle to avoid missing events during At. This method is widely used in modern information modeling systems and complexes. However, as the practice of using similar systems suggests, a single run of combat actions model by groupings at the operational (operational-strategic) level takes considerable hardware resources and operation time.

Another method of formalizing system functioning is the method of essential states, or the by-event method. The point is that the modeled system is split into groups of single-type elements with the same pattern of behavior in time and space. The system functioning process is reproduced by means of discovering instants of event happening and simulation of events in the chronological order.

This method involves a deal of difficulty when developing the algorithm and program of model realization, because in some cases it is not easy to pinpoint the instants when certain events begin and end.

In this connection, we think, it is expedient to use a combined method when the by-event method is applied to actions by opposing forces and assets in a remote zone (e.g., within the range of prospective long-range SAM (surface to air missile) systems), while the Δt method is used for nearby ones (within the effective range of medium- and short-range SAM systems).

In the simulation modeling of combat actions one should also take into account the factors of the situation, which can be formalized and quantified. Because some factors still cannot be accurately estimated by means of formalizing, the results of modeling will be somewhat different from what was expected. The main idea of simulation models is, therefore, typically not forecasting absolute results, but obtaining data for comparing various options (methods) of actions by troops/forces and selecting the best one. In other words, the modeling of actions by assault and defensive forces should be approached in a multivariant fashion, which is widely used in the practice of solving many problems of troop command and control.

One of the more important issues in the creation of simulation models is the choice and justification of the method to reproduce the opposing parties’ combat actions dynamics. The combat actions dynamics can be represented as a process of spatiotemporal change in the state of elements of opposing troop/force groupings. The change in the state of elements can occur under the influence of both external factors, e.g., adversary’s actions, and the C2 actions exercised by officials at C2 bodies. In order to reproduce the combat actions dynamics more adequately it is necessary to solve two problems – pinpoint the instants when elements change their state and assess the results of their transition to new states.

The highly detailed source data, the considerable volume of information processing, and consequently, the fairly long time of modeling are the reasons why simulation models are used chiefly for training operational (combat) crews at Command and Control Centers (command posts) of ASF formations, to prepare and conduct command and staff army games, where the factor of time is not very important. Among the positive sides of simulation models used in troop training can be named the fact that they encourage the development of situational thinking in military C2 officials, and also help better predict the likely course of events. Besides, this is virtually the only instrument for obtaining normative coefficients to be used in other model types.

Taking a well-grounded decision and planning combat actions will require an all-round assessment of the combat potential and fighting efficiency of ASF formations. To this end, there should be envisaged a chance of obtaining and analyzing the results of modeling for the required period. Preserving the modeling results for actions by the opposing parties in each period, it is possible to get any automated selection characterizing the result change dynamics in combat actions.

Among the basic indicators discovered in the course of combat actions modeling for the opposing parties may be included the following: the parties’ force correlation; the efficiency of combat actions, given the implemented fighting potential of troop/force groupings, that characterizes the damage to the adversary inflicted on the ground, at sea, and in the air; the efficiency of air (aerospace) defense of the covered assets, and trop/force groupings, that characterizes the averted damage to facilities or the degree of combativity preserved in the covered troop/force groupings; the losses of the parties on the ground, in the air, and in aerospace.

The indicators listed above are identified by combat actions stage, sector, military formation, and on the whole.

When assessing the modeling results, one can use the following criteria and standards:

• minimum strength of assault forces and assets for achieving the necessary damage to adversary facilities and troop/force groupings;
• maximum damage inflicted on the adversary’s facilities and troop/force groupings by the available combat strength of troops/forces;
• maximum damage inflicted on the adversary aerospace attack weapons (ASAW) by the air and surface-to-air missile forces and assets;
• threshold values of the damage degree probability for adversary facilities, i.e. damage, inactivation, destruction;
• maximum probability of adversary ASAW destruction by ASF forces and assets;
• maximum distance between adversary ASAW destruction range and defense facilities;
• threshold value of damage inflicted on adversary ASAW to achieve the objective of combat actions by ASF military formations (repulsing massive missile and aircraft strikes, repulsing (frustrating) adversary air assault operations);
• temporal parameters of the normative nature (the time of alerting and the time of restoring the fighting efficiency of units and formations, the time of preparing air units and formations for repeat sorties, the firing cycle of mobile SAM systems, etc.).

Examining the ASF composition and tasks, the content of combat actions by various army formations, the modeling processes, the main computational indices and criteria employed, one can draw the following conclusions.

• First, actions by heterogeneous ASF troop and force groupings as a modeling object constitute an aggregate of time-extended consecutive and simultaneous, coordinated and interrelated combat, reconnaissance and information-driven, and support actions performed according to a single idea and plan. To model similar actions, it is necessary to have a set of functionally and informationally interconnected mathematical models, as well as information and computation operational-tactical tasks.
• Second, the makeup and structure of the simulation models and design operational-tactical tasks complex should be substantiated with a view to the identity of actions content for heterogeneous forces and assets of the opposing parties.
• Third, actions by homogeneous ASF forces and assets, for instance, the SAM Forces, are identical to those by similar forces and assets of other services (arms) of the armed forces, including of the adversary. In this context, when simulating actions by homogeneous forces and assets, it is necessary to use uniform indices and methods of their calculation (computation).
• Fourth, in making a justified decision and combat actions planning, one of the most important tasks of troop/force command and control is efficiency assessment of the ASF troop/force groupings actions by operation (combat action) stage. In the interests of solving this problem, there should be a chance of obtaining and analyzing the results of modeling (computation) for each stage of the operation (combat action) or for the established period of time. Therefore, action simulation for the opposing parties should be made in an interactive mode involving the means of human operator-computer program interaction.
• Fifth, the effectiveness of using simulation models and computation operational-tactical tasks largely depends on the correct analysis and assessment of modeling and computation results.

Analysis of modeling results is mental exploration of the data about situation elements and combat actions by the assault and defensive forces of the opposing parties. We propose making the analysis in three stages.

• Stage one is interpretation of the results of modeling and computation, which includes defining the operational-tactical (operational) meaning of the obtained indicator values; estimating the suitability of the modeling (computation) results for use; forming an idea of individual properties of the processes under examination.
• Stage two is quantitative analysis of the modeling results; it consists in assessing the credibility of the results obtained and basing an overall idea of the processes on that. The quantitative estimate of result authenticity is performed with a view to the degree of completeness, importance, and accuracy of reflecting situation factors in the models (design tasks).
• Stage three is qualitative analysis of the results, which includes selection of quality indicators (strong, weak, sufficient, reliable, etc.); establishment of rules for transition from quantitative to qualitative indices; formation (drawing) of conclusions. To switch over from quantitative indices to qualitative ones, one uses criteria of the normative nature. Once the results have been qualitatively assessed, one formulates conclusions for devising suggestions on troop/force combat actions methods.

Thus introduction of interactive simulation models helps officials interfere in the modeling process in order to adjust actions by the opposing parties.

The employment of modern information technologies, accessibility of highperformance computers, and also the available theoretical and practical groundwork for the mathematical modeling of actions by opposing parties’ forces and assets in aerospace armed struggle allowed the staff of the Marshal G.K. Zhukov Military Aerospace Defense Academy in Tver (MADA) to devise the Kolchuga 7.0 modeling unit (MU). It is based on the method of armed struggle simulation modeling.

The Kolchuga 7.0 MU helps automate the following major processes:

• creating and displaying information models of the operational situation in any part of the Earth and circumterrestrial space, including in 3D graphics;
• making information models of weapons and military hardware systems;
• modeling combat actions by the opposing parties’ troops/forces in aerospace;
• computation estimates of troop/force groupings combat potentials;
• conducting autonomous and comprehensive training sessions with crews of Academy training command posts.

The unit is used in the teaching process to prepare and conduct command and staff army games and exercises, and also as an experimental research stand for testing algorithmic and program-technical solutions in the interests of modernizing the ASF automated control system.

Kolchuga 7.0 was pronounced the best project of the innovative developments by RF MOD military schools at Innovation Day of the RF Ministry of Defense in October 2015 as a result of the contest.

A promising trend in improving simulation models, as we see it, is employment of geo-information technologies (GIT), which possess two distinctive features, i.e. a high degree of integration and maximum friendliness.

This fact makes the geo-information technology a key IT. Its especial value can be expressed by the phrase “GIT affords a new view of the world around us.” To create objects of different types and perform various operations with them at the combat preparation and modeling stages GIT can ensure the following.

Formation and display of information about variously localized objects (point, linear, areal, spatial) in real time.

Organization and implementation of an interactive (dialog) regime between the human and the modeling medium in the object state changing dynamics.

Fig; Order of implementing GIT functional scope (version)

The figure shows a version of implementing the GIT functional scope in the course of preparing and conducting ASF military C2 bodies’ training.

In conclusion it has to be said that further development of the combat actions and troop C2 processes simulation modeling method is to be regarded as a major condition of attaining high efficiency in military formation employment, and improving the standards of operational and combat training for C2 bodies of the Aerospace Forces formations.

Translated by Margarita Kvartskhava