Ground search unit distribution algorithm based on genetic algorithm

Abstract

The invention relates to a ground search unit potential distribution algorithm based on a genetic algorithm. The algorithm comprises steps of building a potential distribution model of a unit through search region modeling and search unit modeling, taking the shortest time of the unit arriving at a spacecraft as a target, and taking a grid, located in a safe region, of an initial deployment position of the unit as a constraint condition; and converting the distribution problem of the unit into a mathematical optimization problem, and finally solving by using a genetic algorithm and a multi-resolution method to obtain a distribution scheme. According to the method, a mathematical theoretical basis is provided for the distribution problem of the ground search team, a problem of distribution scheme calculation is solved by using the genetic algorithm, solving efficiency is improved through the multi-resolution grid technology, safety of the team is ensured, search efficiency of the team is improved, and the time required for completing a task is shortened.

Description

technical field [0001] The invention relates to the field of space search and rescue, in particular to a genetic algorithm-based ground search team layout algorithm. Background technique [0002] With the in-depth advancement of my country's manned spaceflight project and lunar exploration project, search and recovery tasks such as manned spacecraft return capsules and lunar exploration return vehicles are showing a trend of high frequency, normalization, and increased emergency incidents, which requires the aerospace ground search team to be able to Quickly arrive at the landing point of the returner and complete the search mission efficiently. The deployment of the ground search team refers to the deployment of each team's standby position before the start of the space search mission. [0003] The existing ground search team layout method is based on factors such as the aiming point of the returner, the landing area, and the performance of the search team's vehicles, and is...

AI Technical Summary

Problems solved by technology

[0004] 1. Due to the lack of systematic theoretical support, there are shortcomings of insufficient scientificity;

[0005] 2. Since the search performance cannot be quantified, it is impossible to quantitatively evaluate the pros and cons of the search scheme

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