Research on the weapon target assignment problem in the combined air defense missile system for training simulation

In modern warfare, when the weapon system and the targets are constantly being improved and upgraded, ensuring the distribution of firepower to optimally destroy the target will help the commander to make quick and accurate decisions, thereby improving combat effectiveness. This paper proposes a method to build a command-control automatic system based on solving the weapon target assignment (WTA) problem in a combination of short and medium-range air defense missile systems so that the total damage of targets is maximum and the damage of protected area is minimum. Based on combinatorial optimization algorithms, the probability of kill, linear programming method using Hungarian algorithm, the paper presents a mathematical model of WTA and its optimal solution for short- and medium-range air defense missile systems serving the training simulation problem, thereby giving the results of evaluating the effectiveness of the algorithm.

Target Assignment for Cooperative Quadrotors Unmanned Aerial Vehicles

The target assignment for cooperative Unmanned aerial vehicles is a critical topic. Most target assignment approaches yield computational complexity when dealing with multiple UAVs. This work offers target assignment approaches and resolves multiple UAVs problems by introducing a proposal of target assignment approaches. The main contribution of this work is solving the target assignment problem using optimal time approach and gain maximization approach in double stages. At the first stage, the urgently desired target to be fetched from the detected target group is selected by using the proposed objective function based on three attribute values of targets (threating weight - importance weight - separating distance). At the second stage, the proposed objective function is used and assign related UAVs for selected desired targets by considering the coverage factors, adaptive-limitation and constrains.

Self-Adaptive Multi-Task Differential Evolution Optimization: With Case Studies in Weapon–Target Assignment Problem

Multi-task optimization (MTO) is related to the problem of simultaneous optimization of multiple optimization problems, for the purpose of solving these problems better in terms of optimization accuracy or time cost. To handle MTO problems, there emerges many evolutionary MTO (EMTO) algorithms, which possess distinguished strategies or frameworks in the aspect of handling the knowledge transfer between different optimization problems (tasks). In this paper, we explore the possibility of developing a more efficient EMTO solver based on differential evolution by introducing the strategies of a self-adaptive multi-task particle swarm optimization (SaMTPSO) algorithm, and by developing a new knowledge incorporation strategy. Then, we try to apply the proposed algorithm to solve the weapon–target assignment problem, which has never been explored in the field of EMTO before. Experiments were conducted on a popular MTO test benchmark and a WTA-MTO test set. Experimental results show that knowledge transfer in the proposed algorithm is effective and efficient, and EMTO is promising in solving WTA problems.

Devising a procedure for justifying the need for samples of weapons and weapon target assignment when using a reconnaissance firing system

This paper proposes an algorithm to substantiate the need for weapons samples, as well as targeting when using a reconnaissance firing system taking into consideration the peculiarities of functioning of such systems. The algorithm essentially implies streamlining the stages in determining the magnitude of the reduction of the enemy's combat potential and, on its basis, the formation of the need for the number of weapons by type. The algorithm makes it possible to take into consideration the nonlinearity of functions that describe both different types of weapons and targets. In addition, this algorithm is based on a modified method of nonlinear programming (two functions). The modification involves the use of a normalized share of the weight of each target as weight coefficients. This allows for targeting while taking into consideration the established level of the combat potential of an enemy. A procedure for determining the need for samples of weapons and targeting in the use of reconnaissance firing systems has been devised. It was determined that in order to achieve the goal of enemy fire damage, it is not typically necessary to use all weapons samples. In general, the procedure makes it possible to take into consideration the peculiarities of the samples of weapons and their suitability to hit a certain target. That could prevent problems with overspending of resources, failures in the detection-defeat cycle, non-fulfillment (not fully performing) tasks during enemy fire damage. In general, the algorithm and procedure for determining the need for the samples of weapons and targeting when using a reconnaissance firing system testify to devising a methodology for justifying the need for weapons samples and targeting. The performance and adequacy of this procedure have been tested by considering an example of determining the need for weapons samples and targeting and obtaining the result confirmed by the experience in the use of reconnaissance firing systems