Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep\n Neural Network

2021/11/04 by Joao P. A. Dantas, Andre N. Costa, Dantas, Joao P. A. +7
Engineering · #Aerospace and Aviation Technology #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Guidance and Control Systems #Machine Learning (cs.LG) #Military Defense Systems Analysis

paper · pdf · doi:10.48550/arxiv.2111.04474

openalex publication_date 2021/11/04 · openalex created_date 2022/10/27 · openalex updated_date 2026/07/28

Abstract

This work investigates the use of a Deep Neural Network (DNN) to perform an\nestimation of the Weapon Engagement Zone (WEZ) maximum launch range. The WEZ\nallows the pilot to identify an airspace in which the available missile has a\nmore significant probability of successfully engaging a particular target,\ni.e., a hypothetical area surrounding an aircraft in which an adversary is\nvulnerable to a shot. We propose an approach to determine the WEZ of a given\nmissile using 50,000 simulated launches in variate conditions. These\nsimulations are used to train a DNN that can predict the WEZ when the aircraft\nfinds itself on different firing conditions, with a coefficient of\ndetermination of 0.99. It provides another procedure concerning preceding\nresearch since it employs a non-discretized model, i.e., it considers all\ndirections of the WEZ at once, which has not been done previously.\nAdditionally, the proposed method uses an experimental design that allows for\nfewer simulation runs, providing faster model training.\n

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