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信号源的极极几何模型二维三角剖分。

2D Triangulation of Signals Source by Pole-Polar Geometric Models.

机构信息

Web Engineering and Early Testing (IWT2) research group, Departamento de Lenguajes y Sistemas Informáticos, Escuela Técnica Superior de Ingeniería Informática, Universidad de Sevilla, Avda. Reina Mercedes s/n, 41012 Seville, Spain.

Departamento de Informática Centro de Tecnologia, Universidade Estadual de Maringá, Av. Colombo, 5790 - Jd. Universitário, Maringá 87020-900, Brazil.

出版信息

Sensors (Basel). 2019 Feb 27;19(5):1020. doi: 10.3390/s19051020.

DOI:10.3390/s19051020
PMID:30818879
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6427499/
Abstract

The 2D point location problem has applications in several areas, such as geographic information systems, navigation systems, motion planning, mapping, military strategy, location and tracking moves. We aim to present a new approach that expands upon current techniques and methods to locate the 2D position of a signal source sent by an emitter device. This new approach is based only on the geometric relationship between an emitter device and a system composed of m≥2 signal receiving devices. Current approaches applied to locate an emitter can be deterministic, statistical or machine-learning methods. We propose to perform this triangulation by geometric models that exploit elements of pole-polar geometry. For this purpose, we are presenting five geometric models to solve the point location problem: (1) based on centroid of points of pole-polar geometry, PPC; (2) based on convex hull region among pole-points, CHC; (3) based on centroid of points obtained by polar-lines intersections, PLI; (4) based on centroid of points obtained by tangent lines intersections, TLI; (5) based on centroid of points obtained by tangent lines intersections with minimal angles, MAI. The first one has computational cost On and whereas has the computational cost Onlognwhere n is the number of points of interest.

摘要

二维点定位问题在多个领域有应用,例如地理信息系统、导航系统、运动规划、映射、军事策略、位置和跟踪运动。我们旨在提出一种新的方法,该方法扩展了当前的技术和方法,以定位由发射器设备发送的信号源的二维位置。这种新方法仅基于发射器设备和由 m≥2 个信号接收设备组成的系统之间的几何关系。当前应用于定位发射器的方法可以是确定性的、统计性的或机器学习方法。我们提议通过利用极极几何元素的几何模型来执行这种三角测量。为此,我们提出了五个解决点定位问题的几何模型:(1)基于极点极线几何的质心,PPC;(2)基于极点点之间的凸包区域,CHC;(3)基于极线交点的点的质心,PLI;(4)基于切线交点的点的质心,TLI;(5)基于切线与最小角交点的点的质心,MAI。第一个模型的计算成本为 On,而第二个模型的计算成本为 Onlogn,其中 n 是感兴趣的点数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/098a88506a8b/sensors-19-01020-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/ce160f22c3b3/sensors-19-01020-g0A1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/641bf4abc747/sensors-19-01020-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/fe0a8b5d818b/sensors-19-01020-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/528b4de09c33/sensors-19-01020-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/675300fdeae6/sensors-19-01020-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/7ccf966e7bba/sensors-19-01020-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/97e987f9656e/sensors-19-01020-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/0af32430b6d5/sensors-19-01020-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/8f9270c6778c/sensors-19-01020-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/5536a9b613eb/sensors-19-01020-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/dd706ddbdc2c/sensors-19-01020-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/28d80904c7fd/sensors-19-01020-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/93e5fe1c0df3/sensors-19-01020-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/ff10c300fd78/sensors-19-01020-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/514e4655086b/sensors-19-01020-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/7e93b2aa204e/sensors-19-01020-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/152bf1cd626c/sensors-19-01020-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/098a88506a8b/sensors-19-01020-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/ce160f22c3b3/sensors-19-01020-g0A1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/641bf4abc747/sensors-19-01020-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/fe0a8b5d818b/sensors-19-01020-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/528b4de09c33/sensors-19-01020-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/675300fdeae6/sensors-19-01020-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/7ccf966e7bba/sensors-19-01020-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/97e987f9656e/sensors-19-01020-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/0af32430b6d5/sensors-19-01020-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/8f9270c6778c/sensors-19-01020-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/5536a9b613eb/sensors-19-01020-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/dd706ddbdc2c/sensors-19-01020-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/28d80904c7fd/sensors-19-01020-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/93e5fe1c0df3/sensors-19-01020-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/ff10c300fd78/sensors-19-01020-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/514e4655086b/sensors-19-01020-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/7e93b2aa204e/sensors-19-01020-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/152bf1cd626c/sensors-19-01020-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5151/6427499/098a88506a8b/sensors-19-01020-g017a.jpg

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