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Particle swarm optimization-based particle filter for cooperative localization in wireless networks

机译:基于粒子群优化的粒子滤波在无线网络中的协同定位

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We propose a novel cooperative localization algorithm called PSO-PF algorithm based on particle swarm optimization enhanced particle filter that fuses information from both anchors with known positions and agents with unknown positions in wireless networks. The proposed algorithm for localization is fully distributed and can eliminate the loss of diversity caused by resampling in particle filter. Simulation results show that the proposed algorithm outperforms the particle filter on the accuracy with less particles in the challenged scenarios for cooperative localization. Moreover, the proposed algorithm is superior performance on convergence to the particle filter in cooperative localization.
机译:我们提出了一种基于粒子群优化增强粒子滤波器的新型协作定位算法PSO-PF算法,该算法融合了来自无线网络中已知位置的锚点和未知位置的代理的信息。所提出的定位算法是完全分布式的,并且可以消除由于粒子滤波中的重采样而导致的分集损失。仿真结果表明,所提出的算法在挑战性场景下的协同定位性能优于粒子滤波器,粒子数量较少。此外,该算法在协同定位方面优于粒子滤波器。

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