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- W3151849923 abstract "Recently, passive unmanned aerial vehicle (UAV) localization has become popular due to mobility and convenience. In this paper, we consider a scenario of using distributed drone cluster to estimate the position of a passive emitter via received signal strength (RSS). First, a distributed majorizeminimization (DMM) RSS-based localization method is proposed. To accelerate its convergence, a tight upper bound of the objective function from the primary one is derived. Furthermore, to reduce communication overhead, a distributed estimation scheme using the Fisher information matrix (DEF) is presented, with only requiring one-round communication between edge UAVs and center UAV. Additionally, a local search solution is used as the initial value of DEF. Simulation results show that the proposed DMM performs better than the existing distributed Gauss-Newton method (DGN) in terms of root of mean square error (RMSE) under a limited low communication overhead constraint. Moreover, the proposed DEF performs much better than MM in terms of RMSE, but has a higher computational complexity than the latter." @default.
- W3151849923 created "2021-04-13" @default.
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- W3151849923 date "2021-04-01" @default.
- W3151849923 modified "2023-09-25" @default.
- W3151849923 title "Communication-efficient Coordinated RSS-based Distributed Passive Localization via Drone Cluster" @default.
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- W3151849923 doi "https://doi.org/10.48550/arxiv.2104.00490" @default.
- W3151849923 hasPublicationYear "2021" @default.
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