Unmanned aerial vehicle complete search path planning method based on reciprocating backfill algorithm

Abstract

The invention relates to an unmanned aerial vehicle complete search path planning method based on a reciprocating backfill algorithm, and the method comprises the steps: building an environment model of a search region, and determining an initial search point of an unmanned aerial vehicle; selecting an orientation priority mode, and performing backfill reciprocating search on the search region in response to selection of the first orientation priority mode; in response to the selection of a second orientation priority mode, performing an L-type reciprocating search on the search region; in the searching process, when the unmanned aerial vehicle enters the dead zone, judging whether the current searching coverage rate reaches the preset minimum searching coverage rate or not, and if so, ending the searching; and if not, planning a path to jump out of the dead zone by using an A star algorithm, and then continuing to search according to the selected orientation priority mode. According to the method, by improving a reciprocating search strategy and adding a backfilling mechanism, the use frequency and the turn-round frequency of the A star algorithm are greatly reduced while the low repetition rate is guaranteed, so that resource consumption is reduced, and the search efficiency is further improved.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a method for planning a complete search path of an unmanned aerial vehicle based on a reciprocating backfill algorithm. Background technique [0002] With the needs of modern military, drones have become an indispensable part of high-tech information warfare in recent years. With the increase of UAV payload and the improvement of radar miniaturization technology, airborne radar has gradually become an important part of UAV load, which improves the combat performance of UAV. In terms of search and detection, it is of great significance to study how to reasonably plan the route of UAVs to detect the largest area in the shortest time. [0003] So far, path planning algorithms have been deeply researched and widely used in various fields. Existing path planning with complete coverage is mainly realized by search strategy and heuristic algorithm. Common search strategies ...

AI Technical Summary

Problems solved by technology

When the UAV is in an ideal environment with fewer obstacles, the search efficiency of these strategies is high. However, in practical applications, the battery capacity of the airborne radar equipment is limited. In order to ensure the success rate of the search mission, the limited radar resources must be used. Reasonable use, the above method in the face of the actual complex environment, due to the failure to provide timely feedback on the leftover areas in the search, can not make up for the leftover areas in an efficient way, often resulting in high repetition rates, Too long time, too many U-turns, easy to fall into dead zone, etc.

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