四元数領域Super MDSによる3次元位置推定
Quaternion Domain Super MDS for 3D Localization
無線センサーネットワーク向けに、3次元座標を四元数で表現し、距離と角度情報を統合した低ランク行列でノイズを抑える低計算量の3次元位置推定法を提案した論文。
著者: Keigo Masuoka, Takumi Takahashi, Giuseppe Thadeu Freitas de Abreu, Hideki Ochiai
分類: eess.SP, cs.RO, math.MG
原文アブストラクト
We propose a novel low-complexity three-dimensional (3D) localization algorithm for wireless sensor networks, termed quaternion-domain super multidimensional scaling (QD-SMDS). This algorithm reformulates the conventional SMDS, which was originally developed in the real domain, into the quaternion domain. By representing 3D coordinates as quaternions, the method enables the construction of a rank-1 Gram edge kernel (GEK) matrix that integrates both relative distance and angular (phase) information between nodes, maximizing the noise reduction effect achieved through low-rank truncation via singular value decomposition (SVD). The simulation results indicate that the proposed method demonstrates a notable enhancement in localization accuracy relative to the conventional SMDS algorithm, particularly in scenarios characterized by substantial measurement errors.