Self-organized Path Planning And Effectiveness Evaluation Methods For Unmanned Aerial Vehicle Swarm Area Coverage Surveillance

Unmanned aerial vehicle(UAV)swarms,characterized by high flexibility,robustness,and low economic cost,have various mission capability.Among all kinds of missions of UAV swarms,area coverage surveillance is an important one that demonstrates their unique advantages.Path planning is a critical issue of area coverage surveillance,and the self-organized path planning method is a typical method characterized by strong adaptivity to dynamic environments.Based on self-organized path planning research,further evaluating swarm surveillance effectiveness when adopting self-organized paths can provide important references to the design,evaluation,and deployment of swarms.This dissertation studies the self-organized surveillance path planning and effectiveness evaluation problems of UAV swarm area coverage surveillance.The research contents are as follows.(1)To establish the framework of the research,the characteristics of area coverage surveillance missions are studied,two typical mission scenarios are selected,including a ground surveillance scenario and a maritime surveillance scenario,then the movement,sensing,communication,and engagement models of combat units are established.In the ground surveillance mission,a swarm provides surveillance support to ground troops,looking for terrorists intended to ambush,and guiding the fire of artilleries to strike them.In the maritime surveillance mission,a swarm assists a patrol ship to look for illegal ships and capture them,preventing them from attacking civilian ships.The movement of combat units is modelled by the three-degree-of-freedom motion equations.The detection ratio of targets is calculated by the Johnson criteria.The communication range and the transmission success ratio are selected as major performance metrics to describe the communication of path planning information among UAVs.The engagement of troops is modelled by the Lanchester equations,and the attack of anti-UAV weapons is described by the non-feedback shooting model.(2)The System-of-systems-supported and Reservation-based Self-organized(So S-RSO)path planning method is proposed.To improve the lacking of considering So S operations in previous works,an update mechanism of convening pheromones under the So S support is proposed,in which target detection effectiveness is improved by utilizing the information support from other combat units in So Ss.To break the restriction of discrete space-time and synchronous decision-making models in previous works,the reservation mechanism is proposed for inter-UAV path coordination,achieving distributed and predictive planning in continuous space-time and asynchronous decision-making conditions.Additionally,the dead zone of trajectories is considered in local path decision-making.The feasibility and advantages in ideal surveillance conditions of the So S-RSO method are demonstrated by simulation.Compared to the sweep method and the self-organized method without So S support,the So S-RSO method can improve the effective target detection ratio by 13.8% and 14.0% respectively in the ground surveillance mission,while by 12.7% and 14.7% respectively in the maritime surveillance mission.(3)Under the idea of agent-based modelling and simulation,the combat modelling and simulation method based on the Agent hierarchical composite behaviour mechanism is proposed as the supporting technology of effectiveness evaluation.To solve the difficulty of realizing self-organized path planning and flight processes under complex mission rules and combat interaction,the Agent hierarchical composite behaviour mechanism is proposed.In the mechanism,missions and behaviours are decomposed into mission states and basic actions respectively,then the three-level composite mechanism controls the execution of basic actions by different rules in different mission states.According to the mechanism,the composable modular model structure is constructed.By the composition and interaction of modules realizing different behaviour segments,the simulation of self-organized swarm area coverage surveillance combat in complex mission scenarios is realized.The simulation programs specific to the typical mission scenarios are developed,demonstrating the applicability,rationality,and correctness of the modelling and simulation method,then showing the advantages of the So S-RSO method in realistic surveillance conditions.Compared to the sweep method and the self-organized method without So S support,the So S-RSO method can improve the effective target detection ratio by 45.8% and 31.1% respectively in the ground surveillance mission,while by 10.4% and 7.7% respectively in the maritime surveillance mission.The So S-RSO method also shows better adaptivity to dynamic events.(4)The hierarchical index system of area coverage surveillance effectiveness evaluation is established preliminarily as the quantitative criteria of effectiveness evaluation.To improve the deficiencies in hierarchy and the inadaptation to area coverage surveillance problems existed in previous works,the index system is established in a hierarchical way based on the generation mechanism of area coverage surveillance effectiveness.In the system scheme level,besides system performance indices,the path efficiency factor is proposed to measure the performance of path planning methods.The swarm capability level measures the coverage capability of swarms,and the indices are decomposed,proposing the time-average effective degree to measure the level of sharing path planning information among UAVs.The swarmeffectiveness level measures the completeness,timeliness,and cost of detecting targets,and the normalized surveillance effectiveness index is proposed as the comprehensive evaluation metric.The simulation demonstrates the feasibility and applicability of the index system.Taking the ground surveillance mission as an example,the simulation shows the advantages of the So S-RSO method in comprehensive effectiveness,whose surveillance effectiveness index is higher than the sweep method and the self-organized method without So S support by 0.28 and 0.22 respectively.The nonmonotonic variation in the surveillance effectiveness of the sweep method and the path efficiency factor in the So S-RSO method are also discovered.(5)Based on the proposed combat modelling and simulation method as well as the proposed effectiveness evaluation index system,taking path planning as a critical element,the effectiveness evaluation method for area coverage surveillance is formulated preliminarily,and it is also preliminarily demonstrated that the effectiveness evaluation method can support the study of So S contribution evaluation.Taking the ground surveillance mission as the focus and the maritime surveillance mission as the verification,simulation experiments are conducted to study the relationships of indices.The number of UAVs is the most important factor for effectiveness,and cruise velocity takes the second place.In the ground surveillance mission,camera resolution shows more significance,while in the maritime surveillance mission,communication performances show more significance.Under inferior communication conditions,the So S-RSO method can still lead to higher effectiveness than the sweep method.In the ground surveillance scenario,compared to improving system performances,improving path planning methods is a batter way to increase effectiveness.The surveillance effectiveness is nonlinearly correlated with the coverage capability,while the overall mission effectiveness of So S is linearly correlated with the swarm surveillance effectiveness.The path efficiency factor is the most significantly influenced by the number of UAVs.For the sweep method,the path efficiency factor decreases with the improvement of system performances,while for the So S-RSO method it is the contrary.When the ratio of the time-average effective degree by the time-average number of in-flight UAVs reaches 75%,the lap of time-average revisit interval by its level in ideal communication conditions can decrease to 10%.The UAV swarm shows great contributions to So S,and the contribution ratio can reach 50.1% and 41.2% in the ground and maritime surveillance mission scenarios respectively.The research shows that,the novel So S-supported reservation-based self-organized surveillance path planning method can be applied to complex So S combat scenarios,and improve the area coverage surveillance effectiveness.With the novel combat modelling and simulation method based on the Agent hierarchical composite behaviour mechanism as well as the novel hierarchical index system of swarm area coverage surveillance effectiveness evaluation,an effective UAV swarm area coverage surveillance effectiveness evaluation method is formulated,and the method can be used to provide references for the design,evaluation,and deployment of UAV swarms.