線形TDOA計測に基づく分散推定と局所化トラッキング
Linear TDOA-based Measurements for Distributed Estimation and Localized Tracking
線形TDOA計測モデルとコンセンサス型データ融合により、疎な通信網上で分散フィルタを設計し、通信負荷を抑えつつ目標追跡を行う手法を提案する。リンクやノード喪失時にも観測可能性を保つ冗長性・耐故障設計の条件も示す。
著者: Mohammadreza Doostmohammadian, Themistoklis Charalambous
分類: eess.SY, cs.MA, cs.RO, cs.SY, eess.SP, math.DS
原文アブストラクト
We propose a linear time-difference-of-arrival (TDOA) measurement model to improve \textit{distributed} estimation performance for localized target tracking. We design distributed filters over sparse (possibly large-scale) communication networks using consensus-based data-fusion techniques. The proposed distributed and localized tracking protocols considerably reduce the sensor network's required connectivity and communication rate. We, further, consider $\kappa$-redundant observability and fault-tolerant design in case of losing communication links or sensor nodes. We present the minimal conditions on the remaining sensor network (after link/node removal) such that the distributed observability is still preserved and, thus, the sensor network can track the (single) maneuvering target. The motivation is to reduce the communication load versus the processing load, as the computational units are, in general, less costly than the communication devices. We evaluate the tracking performance via simulations in MATLAB.
