Priority-based DREAM Approach for Highly Manoeuvring Intruders in A Perimeter Defense Problem

TL;DR

This paper introduces P-DREAM, a priority-based decentralized approach for territory defense against highly maneuvering intruders, combining static optimization and dynamic resource allocation to improve response effectiveness.

Contribution

It develops a novel priority-based extension to the DREAM approach, integrating static optimization with dynamic multi-task assignment for enhanced perimeter defense.

Findings

P-DREAM effectively neutralizes highly maneuvering intruders.

Simulation results show consistent territory protection performance.

Prioritized resource allocation improves response times.

Abstract

In this paper, a Priority-based Dynamic REsource Allocation with decentralized Multi-task assignment (P-DREAM) approach is presented to protect a territory from highly manoeuvring intruders. In the first part, static optimization problems are formulated to compute the following parameters of the perimeter defense problem; the number of reserve stations, their locations, the priority region, the monitoring region, and the minimum number of defenders required for the monitoring purpose. The concept of a prioritized intruder is proposed here to identify and handle those critical intruders (computed based on the velocity ratio and location) to be tackled on a priority basis. The computed priority region helps to assign reserve defenders sufficiently earlier such that they can neutralize the prioritized intruders. The monitoring region defines the minimum region to be monitored and is sufficient enough to handle the intruders. In the second part, the earlier developed DREAM approach is modified to incorporate the priority of an intruder. The proposed P-DREAM approach assigns the defenders to the prioritized intruders as the first task. A convex territory protection problem is simulated to illustrate the P-DREAM approach. It involves the computation of static parameters and solving the prioritized task assignments with dynamic resource allocation. Monte-Carlo results were conducted to verify the performance of P-DREAM, and the results clearly show that the P-DREAM approach can protect the territory with consistent performance against highly manoeuvring intruders.