Beyond Visual Range Research Articles

Simulation and Effectiveness Analysis on One versus One Beyond Visual Range Air Combat

A kind of one versus one beyond visual range (BVR) air combat model has been established, which includes functional models of radar, missile and fighter and the process of several combat stages. Air combat effectiveness ratio (ACER) is defined to analyse the result. The 2k factor design method is used to design combat test case and analyses the influence of three factors (fighter stealth character, missile range and flight height) on ACER. Simulation result reveals that when RCS of one fighter is reduced from 0dBm2 to -10dBm2 which cannot remarkably affect the opposition fighter’s radar detection distance and missile launch distance, the RCS factor has small influence and the missile range factor has great influence. When RCS of one fighter is reduced from -10dBm2 to -20dBm2, the opposition fighter’s radar detection distance will be reduced and lead the result of its missile launch distance be less than its missile range. Compared with the former case, the effect of RCS factor increases and the effect of missile range factor decreases. However, the effect of height is not significant.

A Stochastic Game-Based Approach for Multiple Beyond-Visual-Range Air Combat

This paper addresses tactical decisions in beyond-visual-range (BVR) air combat between two adversarial teams of multiple (autonomous) aircraft. A BVR combat is formalized as a two-player stochastic game consisting of a sequence of normal-form games that determines on the number of missiles to be allocated to each adversary aircraft; within this normal-form game a continuous sub-game is embedded to determine the missile shooting times. The formulation reduces the size of decision space by taking advantage of the underlying symmetry of the combat scenario, and also facilitates incorporation of the effect of cooperative missile maneuvers and transition into within-visual-range (WVR) combat. The Nash equilibrium strategies and the associate value functions of the game are computed through linear-programming-based dynamic programming procedure. Numerical case studies on combat between airplanes with heterogeneous capabilities and cooperation effects demonstrate the validity of the proposed formulation and the effectiveness of the proposed solution scheme.

Development of Air Combat Effectiveness Simulation and Analysis Scheme for beyond Visual Range (BVR) Case

This paper focuses on the simulation of Beyond Visual Range (BVR) Air Combat using calculation of Probability of Kill (PK) and Supremacy to analyze the effectivity of the tactics and strategies. The developed simulation program is expected to be used as a means of developing tactics, weapons systems evaluation and to support other air combat system applications. The simulation system can be utilized so that strategy for using weapons and better tactics for maneuver can be determined and formulated in the face of an aerial battle. The simulation illustrates how an aerial battle in a 2D plane took place. The battle occurs between two sides and can also cover case of many against many air battle. Fighters maneuver will be generated based on logic and defined tactic by providing input in the form of initial conditions. Formulation / functions, parameters and variables influencing the fighter effectiveness will be taken into account. These elements are modelled using a dynamic and open scenario approach. The simulation used a method called 'Missile Launch Envelope Model' for computing PK of missile along its way to the target. Simulation results for one versus one and many versus many cases show that the developed system can produce good and relatively realistic prediction of the outcome. Further modification of simulation program include fly out modeling to the missile.

HEURISTIC QUANTUM GENETIC ALGORITHM FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

In order to achieve the optimal attack outcome in the air combat under the beyond visual range (BVR) condition, the decision-making (DM) problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack (CMTA). In this paper, a heuristic quantum genetic algorithm (HQGA) is proposed to solve the DM problem. The originality of our work can be supported in the following aspects: (1) the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits (Q-bits); (2) the relative successful sequence probability (RSSP) is defined, based on which the priority attack vector is constructed; (3) the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper; (4) last but not the least, in some special conditions, the HQGA gets rid of the constraint described by other algorithms that to obtain a better result. In the end of this paper, two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.

A Model of Tactic Threat Assessment in PAAIS

The tactical situation assessment is the basis of Mission Planning, Emergency Action Planning, Firepower Assignment and Attack Ordering in PAAIS (Pilot Assistant Artificial Intelligent System). To take into account the current BVR (Beyond-Visual-Range) air combat threat assessment, we proposed a method which used the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) arithmetic to evaluate the air target threat. Compared to the other threat methods, this arithmetic has the characteristic of simple, computation fast, update expediently and so on. The simulation result indicated that it can respond quickly to the detected targets and satisfy the requirement of situation assessment in PAAIS.