Cooperative allocation and guidance for air defence application

Signal and Data Processing of Small Targets 2008, 2008

In this paper, both Pareto game theory and learning theory algorithms are utilized in a resource management module for a practical missile interception system. The resource management module will determine how many and which antimissiles will be launched for interception. Such interception decisions are based on the number of invading missiles, availability of antimissiles, special capability of antimissiles, and realistic constraints on the movements of both invading missiles and antimissiles such as minimum turning radius, maximum velocity, fuel range, etc. Simulations demonstrate performance improvements when compared to existing strategies (i.e. random assignment), independent of guidance laws (i.e. Proportional Navigation (PN) or the Differential-Game-based Guidance Law (DGL) guidance laws) under endgame interception cases or midcourse interception situations. Downloaded From: http://spiedigitallibrary.org/ on 10/22/2013 Terms of Use: http://spiedl.org/terms Proc. of SPIE Vol. 6969 69690N-4 Downloaded From: http://spiedigitallibrary.org/ on 10/22/2013 Terms of Use: http://spiedl.org/terms

2009

This paper proposes and implements biologically inspired architectures like Genetic algorithm(GA), Reinforcement algorithm and Particle swarm optimization (PSO) algorithm to solve the weapon allocation problem in the Multi layer defense scenario. The proposed schemes were implemented in MATLAB and the percentage of assets saved has increased. In the experimental analysis training time is drastically reduced. PSO was shown to converge rapidly and resulted in saving more assets with faster convergence of learning.

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009

Dynamic programming has recently received significant attention as a possible technology for formulating control commands for decision makers in an extended complex enterprise that involves adversarial behavior. Enterprises of this type are typically modeled by a nonlinear discrete time dynamic system. The state is controlled by two decision makers, each with a different objective function and different hierarchy of decision making structure. To illustrate this enterprise, we derive a state space dynamic model of an extended complex military operation that involves two opposing forces engaged in a battle. The model assumes a number of fixed targets that one force is attacking and the other is defending. Due to the number of control commands, options for each force, and the steps during which the two forces could be engaged, the optimal solution for such a complicated dynamic game over all stages is computationally extremely difficult, if not impossible, to propose. As an alternative, we propose an expeditious suboptimal solution for this type of adversarial engagement. We discuss a solution approach where the decisions are decomposed hierarchically and the task allocation is separate from cooperation decisions. This decoupled solution, although suboptimal in the global sense, is useful in taking into account how fast the decisions should be in the presence of adversaries. An example scenario illustrating this military model and our solution approach is presented.

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2000

The purpose of this paper is to propose a solution methodology for a missile defense problem involving the sequential allocation of defensive resources over a series of engagements. The problem is cast as a dynamic programming/Markovian decision problem, which is computationally intractable by exact methods because of its large number of states and its complex modeling issues. We have employed a neuro-dynamic programming (NDP) framework, whereby the cost-to-go function is approximated using neural network architectures that are trained on simulated data. We report on the performance obtained using several different training methods, and we compare this performance with the optimal.

Naval Research Logistics (NRL), 2011

In this study, we present a new formulation for the air defense problem of warships in a naval task group and propose a solution method. We define the missile allocation problem (MAP) as the optimal allocation of a set of surface-to-air missiles (SAMs) of a naval task group to a set of attacking air targets. MAP is a new treatment of an emerging problem fostered by the rapid increase in the capabilities of anti-ship missiles (ASMs), the different levels of air defense capabilities of the warships against the ASM threat, and new technology that enables a fully coordinated and collective defense. In addition to allocating SAMs to ASMs, MAP also schedules launching of SAM rounds according to shoot-look-shoot engagement policy or its variations, considering multiple SAM systems and ASM types. MAP can be used for air defense planning under a given scenario. As thorough scenario analysis would require repetitive use of MAP, we propose efficient heuristic procedures for solving the problem.

Automatica, 2019

Multi-player pursuit-evasion games are crucial for addressing the maneuver decision problem arising in the cooperative control of multi-agent systems. This work addresses a particular pursuit-evasion game with three players, Target, Attacker, and Defender. The Attacker aims to capture the Target, while avoiding being captured by the Defender and the Defender tries to defend the Target from being captured by the Attacker, while trying to capture the Attacker at an opportune moment. A two-pronged pursuit-evasion problem in this game is considered and we focus on two aspects: the cooperation between the Target and Defender and balancing the roles of the Attacker between pursuer and evader. A barrier based on the explicit policy method and geometric analysis method is constructed to separate the whole state space into two disjoint parts that correspond to two winning regions for the Attacker and Target-Defender team. The main contributions of this work are obtaining the players' winning regions and providing a complete game solution by analyzing the optimal strategies and trajectories of the players based on the barrier.

Operations Research, 2005

We describe JOINT DEFENDER, a new two-sided optimization model for planning the pre-positioning of defensive missile interceptors to counter an attack threat. In our basic model, a defender pre-positions ballistic missile defense platforms to minimize the worst-case damage an attacker can achieve; we assume that the attacker will be aware of defensive pre-positioning decisions, and that both sides have complete information as to target values, attacking-missile launch sites, weapon system capabilities, etc. Other model variants investigate the value of secrecy by restricting the attacker's and/or defender's access to information. For a realistic scenario, we can evaluate a completely transparent exchange in a few minutes on a laptop computer, and can plan near-optimal secret defenses in seconds. JOINT DEFENDER's mathematical foundation and its computational efficiency complement current missile-defense planning tools that use heuristics or supercomputing. The model can also provide unique insight into the value of secrecy and deception to either side. We demonstrate with two hypothetical North Korean scenarios.

ANZIAM Journal, 2007

We overview methodologies to optimise an aircraft trajectory in a two-player close air combat scenario. In mathematical terms air combat can be considered as a game. However, due to the highly nonlinear equations of motion involved, the use of classical games theory is difficult to implement in a computer simulation. The search for the saddle point of the game is difficult and therefore an indirect approach is required to search for the best trajectory. At each instance, one player is given the role of evader and the other the pursuer. The evader must find the trajectory that avoids or maximises the time to interception, while the pursuer must find a trajectory that achieves or minimises the time to intercept the evader. An algorithm has been

Dynamic Games and Applications, 2018

A novel pursuit-evasion differential game involving three agents is considered. An Attacker missile is pursuing a Target aircraft. The Target aircraft is aided by a Defender missile launched by, say, the wingman, to intercept the Attacker before it reaches the Target aircraft. Thus, a team is formed by the Target and the Defender which cooperate to maximize the separation between the Target aircraft and the point where the Attacker missile is intercepted by the Defender missile, while at the same time the Attacker tries to minimize said distance. A long-range Beyond Visual Range engagement which is in line with current CONcepts of OPeration is envisaged, and it is therefore assumed that the players have simple motion kinematics á la Isaacs. Also, the speed of the Attacker is equal to the speed of the Defender and the latter is interested in point capture. It is also assumed that at all time the Attacker is aware of the Defender's position, i.e., it is a perfect information game. The analytic/closedform solution of the target defense pursuit-evasion differential game delineates the state space region where the Attacker can reach the Target without being intercepted by the Defender, thus disposing of the Game of Kind. The target defense Game of Degree is played in the remaining state space. The analytic solution of the Game of Degree yields the agents' optimal state feedback strategies, that is, the instantaneous heading angles for the Target and the Defender team to maximize the terminal separation between Target and Attacker at the instant of Electronic supplementary material The online version of this article (

2008 IEEE Aerospace Conference, 2008

Traditional missile interception often focuses on simplified scenarios such as one-to-one or multi-to-one interception. Recently, battlefield situations pose new difficulties for missile defense systems, which make traditional interception systems inefficient. The problems revolve around two aspects: 1) The guidance law insufficiency (traditional forms PN, DGL/1, and DGL/C); and 2) Resource management insufficiency. This paper fuses game theoretic resource management and a noise level related guidance law to existing missile defense system which is called Differential Game Law Type M (DGL/M). Intensive simulations show that this approach demonstrates improvements over existing methods. 1 2