Determining localization from ordinal comparison data

    公开(公告)号:US11356805B2

    公开(公告)日:2022-06-07

    申请号:US16559218

    申请日:2019-09-03

    IPC分类号: H04W24/00 H04W4/029 H04W4/33

    摘要: A method for determining location of a target within an indoor environment, including the steps of: classifying a set of anchors having known locations within the indoor environment and a set of targets having unknown locations within the indoor environment, wherein each of the anchors and targets comprise hardware having sensors and wireless communication capabilities; creating a set of ordinal pair data sets comprising relative distances between each target and all anchors; ranking and aggregating the ordinal pair data sets to produce a set of dissimilarities that approximate distances; transforming the dissimilarities into estimated distances between each anchor and target using the known distances between the anchors as calibration; and inferring location of targets by formulating and solving a multidimensional unfolding optimization.

    Determining Localization from Ordinal Comparison Data

    公开(公告)号:US20200228926A1

    公开(公告)日:2020-07-16

    申请号:US16559218

    申请日:2019-09-03

    IPC分类号: H04W4/029 H04W4/33

    摘要: A method for determining location of a target within an indoor environment, including the steps of: classifying a set of anchors having known locations within the indoor environment and a set of targets having unknown locations within the indoor environment, wherein each of the anchors and targets comprise hardware having sensors and wireless communication capabilities; creating a set of ordinal pair data sets comprising relative distances between each target and all anchors; ranking and aggregating the ordinal pair data sets to produce a set of dissimilarities that approximate distances; transforming the dissimilarities into estimated distances between each anchor and target using the known distances between the anchors as calibration; and inferring location of targets by formulating and solving a multidimensional unfolding optimization.