5G SLAMのための反復事後線形化PMBフィルタ
Iterated Posterior Linearization PMB Filter for 5G SLAM
5Gミリ波信号を用いたSLAMにおいて、測定関数を事後確率密度で線形化する反復事後線形化フィルタをPoisson multi-Bernoulliフィルタに組み込み、精度向上を実現した。
著者: Yu Ge, Yibo Wu, Fan Jiang, Ossi Kaltiokallio, Jukka Talvitie, Mikko Valkama, Lennart Svensson, Henk Wymeersch
分類: eess.SP, cs.RO
原文アブストラクト
5G millimeter wave (mmWave) signals have inherent geometric connections to the propagation channel and the propagation environment. Thus, they can be used to jointly localize the receiver and map the propagation environment, which is termed as simultaneous localization and mapping (SLAM). One of the most important tasks in the 5G SLAM is to deal with the nonlinearity of the measurement model. To solve this problem, existing 5G SLAM approaches rely on sigma-point or extended Kalman filters, linearizing the measurement function with respect to the prior probability density function (PDF). In this paper, we study the linearization of the measurement function with respect to the posterior PDF, and implement the iterated posterior linearization filter into the Poisson multi-Bernoulli SLAM filter. Simulation results demonstrate the accuracy and precision improvements of the resulting SLAM filter.
