Non-uniform gridding monitoring method forunmanned aerial vehicle based on enhanced learning algorithm

Abstract

The invention discloses a non-uniform gridding monitoring method for unmanned aerial vehicle based on enhanced learning algorithm and relates to the field of security and protection in smart city construction. The method comprises the following steps that 1, grading city defense targets according to security, 2, dividing a monitoring area, and taking a target safety level, a terrain factor, a signal interference factor and a confidentiality factor of the monitoring area as main factors; 3, identifying the monitoring area; 4, installing monitoring to form network points; and 5, comprehensivelyevaluating the unmanned aerial vehicle flight probability of grid points, the unmanned aerial vehicle search difficulty and the threat degree of an unmanned aerial vehicle to a target by each index. According to the invention, technologies such as navigation positioning, signal analysis, unmanned aerial vehicle position reporting wireless protocols and the like are combined to realize gridding monitoring of urban low, slow and small unmanned aerial vehicle targets, and a large-range monitoring scheme suitable for urban low, slow and small unmanned aerial vehicles is formed.

Description

technical field [0001] The invention relates to the field of security in smart city construction, and more specifically relates to a non-uniform grid-based unmanned aerial vehicle monitoring method based on an enhanced learning algorithm. Background technique [0002] UAVs originate from the field of military applications and are often used for battlefield reconnaissance and local military strikes. With the development of radio communication and flight control technology, unmanned aerial vehicles are developing in the direction of civilian use and consumer level. At present, drones have been widely used in fields such as news, logistics, energy, search and rescue, and public security, and have become an important country in the global drone manufacturing industry. It is predicted that the global drone market will exceed US$45 billion, and the drones produced by DJI alone account for 70% of the global drone market. [0003] While drones bring convenient services to people, ...

AI Technical Summary

Problems solved by technology

[0006] (3) Threat to the security of the prison at low altitude: the prison’s defense line on the ground is already sufficient, and there is no effective defense method for the low altitude to defend against the use of drones for message transmission, object throwing, and prison escape assistance;

Acoustic detection technology is greatly disturbed by background noise

In addition, the above technical products are limited by the cost of system software and hardware, and cannot be widely used and promoted in cities