Predefined Location Formation: Keeping Control for UAV Clusters Based on Monte Carlo Strategy

Abstract

UAV formation keeping is an important research element due to its cooperative formation control. This study proposes a passive positioning model for UAVs based on the Monte Carlo strategy and provides a trajectory programming decision scheme based on the predicted calculation of deviated UAV predefined endpoint locations, effectively improving the efficiency of UAVs performing formation-keeping tasks during flight. Then, the simulation after sampling by Gaussian distribution is used to obtain the trajectory planning under simultaneous control of multiple cluster formations, and the feasibility, accuracy and stability of the proposed model are verified. This study provides useful guidance for UAV formation control applications.

A Scalable Distributed Control Algorithm for Bearing-Only Passive UAV Formation Maintenance

“…In this contribution, we focused on a general method and principle of UAV formation, without considering a specific UAV model [19,24]. For simplicity, we ignored the processing details and potential transmit error of radiation source signals in comparison to [23]. We also did not model the flight process of UAVs in detail, such as travel speed and flight direction, assuming immediate adjustment to avoid lengthy discussions.…”

“…Maintaining a UAV formation involves a three-dimensional task that is simplified into a two-dimensional task on the horizontal plane. This is achieved by utilizing various physical actuators that monitor the speed and altitude, as noted in [22,23]. To simplify the task, a new coordinate system is constructed with the central UAV as the reference.…”

“…It should be noted that we did not conduct comparative experiments in this section, as to the best of our knowledge, reference [23] is the only paper related to our work. The study aimed to achieve UAV formation maintenance in electromagnetic silence scenarios by minimizing the number of signal-emitting sources, and the assumptions made in that paper are different from ours.…”

A New Method of UAV Swarm Formation Flight Based on AOA Azimuth-Only Passive Positioning

“…Many UAV formation schemes based on passive positioning have been proposed [1][2][3][24][25][26][27][28]. Li et al [3] proposed a moving target passive positioning method based on the A-optimization criterion.…”

“…Li et al [29] proposed a unified formulation to calculate the accuracy factor (DOP). Li et al [24] proposed a passive UAV positioning model based on Monte Carlo strategy in the context of passive positioning, and provided a trajectory planning decision scheme based on predictive computation of predefined endpoint positions of deviating UAVs. Fu et al [25] proposed an analytical geometry-based pure azimuth passive positioning UAV localization and adjustment scheme.…”