# A Low Complexity Persistent Reconnaissance Algorithm for FANET
###### Abstract  
In recent years, with the rapid progress of unmanned aerial vehicle (UAV) technology, UAV-based systems have been widely used in both civilian and military applications. Researchers have proposed various network architectures and routing protocols to address the network connectivity problems associated with the high mobility of UAVs, and have achieved considerable results in a flying ad hoc network (FANET). Although scholars have noted various threats to UAVs in practical applications, such as local magnetic field variation, acoustic interference, and radio signal hijacking, few studies have taken into account the dynamic nature of these threat factors. Moreover, the UAVs' high mobility combined with dynamic threats makes it more challenging to ensure connectivity while adapting to ever-changing scenarios. In this context, this paper introduces the concept of threat probability density function (threat PDF) and proposes a particle swarm optimization (PSO)-based threat avoidance and reconnaissance FANET construction algorithm (TARFC), which enables UAVs to dynamically adapt to avoid high-risk areas while maintaining FANET connectivity. Inspired by the graph editing distance, the total edit distance (TED) is defined to describe the alterations of the FANET and threat factors over time. Based on TED, a dynamic threat avoidance and continuous reconnaissance FANET operation algorithm (TA&CRFO) is proposed to realize semi-distributed control of the network. Simulation results show that both TARFC and TA&CRFO are effective in maintaining network connectivity and avoiding threats in dynamic scenarios. The average threat value of UAVs using TARFC and TA&CRFO is reduced by 3.99-27.51% and 3.07-26.63%, respectively, compared with the PSO algorithm. In addition, with limited distributed moderation, the complexity of the TA&CRFO algorithm is only 20.08% of that of TARFC. unmanned aerial vehicles; FANET; PSO-based; relay node placement; persistent reconnaissance; dynamic threat avoidance; low complexity 20  
in the FANET. Through an exhaustive performance analysis, they have obtained some instructive conclusions. [PERSON] et al. [2] use a specifically designed protocol for FANETs that considers the interest characteristics of FANETs, but the path to destination sometimes is not optimized and creates a closed-loop route. Considering the fast dynamic nature of nodes in FANETs, [PERSON] et al. propose a technique in [3] to use combined directional and Omni-directional antenna to improve routing path selection and try to minimize the Expected Connection Time (EMC) and the utility function for path selection. To accommodate the communication requirements of a heterogeneous network, [PERSON] et al. [4] design an interaction possibility metric in routing protocol. In this way, the protocol improves the extension of networks and coverage of sub-networks assistance to some extent. Focusing on the UAVs' power limitation, [PERSON] [5] structures an energy-efficient cooperative relaying scheme to extend the network lifetime while guaranteeing the success rate. The excellent mobility of nodes in the FANET makes localization, deployment, and timely optimization of paramount importance [6; 7; 8; 9]. The localization of UAVs is a prerequisite for algorithms to maintain network connectivity and threat avoidance, and a well-connected network can also improve localization accuracy through collaboration [6]. In [7], UAVs are envisioned as wireless base stations. The authors first calculated the coverage probability of the downlink, then used circle packing theory to determine UAVs' locations in 3D space to maximize the coverage area and coverage lifetime. Notably, [PERSON] et al. [8] propose a FANET topology coordination protocol based on Software-Defined Network (SDN). By incorporating SDN into the UAV deployment strategy, the article sheds new light on FANET deployment optimization.