Constrained Target Clustering for Military Targeting Process

Abstract

Constrained target clustering (CTC) is proposed to support the targeting decision-making in the network centric warfare environment. When area targets are detected by sensors, it is required to decide the points at which a missile or bomb is aimed to achieve operational goals. CTC can determine the optimal numbers and positions of aiming points by transforming the targeting problem into clustering-based optimisation problems. The CTC formulations include objective functions and constraints in consideration of area targets, protected objects, target-level background information, lethal radius, and required damage rate. The numerical example shows how to apply the CTC formulation given a sample data set. In order to compare the effects of different constraints, the demonstration explores from an unconstraint problem to constrained problems by adding constraints. The results show that CTC can effectively decide the aiming points with consideration of both targets and capabilities of friendly weapons, and serve as a targeting decision support system in the network centric warfare environment.

Constrained Multi-Objective Weapon Target Assignment for Area Targets by Efficient Evolutionary Algorithm

“…where f 1 is the objective that denotes the expected kill probability of the targets; f 2 is the objective that denotes the weapon consumption; m is the number of weapons and n is the number of targets; v j is the survival value of target j which is evaluated by threat evaluation; {p 1 , p 2 , • • • , p n } is the position set of detected hostile targets; A = {a 1 , a 2 , • • • , a m } is the position set of aiming points of weapons; X = (x 1 , x 2 , • • • , x m ) is the decision vector; D(•) is the function of damage effect by the distance between blast points and targets. Based on research involving collateral damage estimate [38], [39], [55]- [58], we assume no firing error and approximate the conditional damage law of target coordinate as…”

“…Bogdanowicz and Patel [38] designed a quick collateral damage estimate (QCDE) algorithm to support WTA capabilities with collateral damage consideration. Ma [39] established the principle of Constrained Target Clustering (CTC), but the number of clusters is set artificially and there is no overlap. Inspired by the above analysis, we formulate a constrained multi-objective weapon target assignment model.…”