CN107396322A - 基于路径匹配与编码译码循环神经网络的室内定位方法 - Google Patents
基于路径匹配与编码译码循环神经网络的室内定位方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Cited By (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108399201A (zh) * | 2018-01-30 | 2018-08-14 | 武汉大学 | 一种基于循环神经网络的Web用户访问路径预测方法 |
CN108629978A (zh) * | 2018-06-07 | 2018-10-09 | 重庆邮电大学 | 一种基于高维路网和循环神经网络的交通轨迹预测方法 |
CN108957502A (zh) * | 2018-06-04 | 2018-12-07 | 安徽理工大学 | 基于深度学习lstm的gnss多***多路径误差实时削弱方法 |
CN108984904A (zh) * | 2018-07-17 | 2018-12-11 | 北京理工大学 | 一种基于深度神经网络的家居设计方法 |
CN109620154A (zh) * | 2018-12-21 | 2019-04-16 | 平安科技(深圳)有限公司 | 基于深度学习的肠鸣音识别方法及相关装置 |
CN110174690A (zh) * | 2019-05-30 | 2019-08-27 | 杭州中科微电子有限公司 | 一种基于长短期记忆网络辅助的卫星定位方法 |
CN110290466A (zh) * | 2019-06-14 | 2019-09-27 | ***通信集团黑龙江有限公司 | 楼层判别方法、装置、设备及计算机存储介质 |
CN110334741A (zh) * | 2019-06-06 | 2019-10-15 | 西安电子科技大学 | 基于循环神经网络的雷达一维距离像识别方法 |
CN110519693A (zh) * | 2019-09-29 | 2019-11-29 | 东北大学 | 一种面向智能移动终端的融合定位方法 |
CN110533166A (zh) * | 2019-08-21 | 2019-12-03 | 中山大学 | 一种基于时空间融合特征的室内定位方法 |
CN111372182A (zh) * | 2018-12-06 | 2020-07-03 | ***通信集团陕西有限公司 | 一种定位方法、装置、设备及计算机可读存储介质 |
EP3764120A1 (en) * | 2019-07-10 | 2021-01-13 | Swisscom AG | Low power wide area network localization |
CN112930484A (zh) * | 2018-10-31 | 2021-06-08 | 三菱电机株式会社 | 定位***、定位方法和存储介质 |
CN112994840A (zh) * | 2021-02-03 | 2021-06-18 | 白盒子(上海)微电子科技有限公司 | 一种基于神经网络的译码器 |
CN113051976A (zh) * | 2019-12-27 | 2021-06-29 | 广东博智林机器人有限公司 | 指纹定位方法、装置、电子设备及存储介质 |
CN113347559A (zh) * | 2021-05-14 | 2021-09-03 | 武汉大学 | 一种基于深度学习的强鲁棒性无线定位方法 |
CN114510044A (zh) * | 2022-01-25 | 2022-05-17 | 北京圣威特科技有限公司 | Agv导航船导航方法、装置、电子设备及存储介质 |
CN114631365A (zh) * | 2020-01-02 | 2022-06-14 | 三星电子株式会社 | 检测位置的电子装置及其方法 |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8077090B1 (en) * | 2010-06-15 | 2011-12-13 | Microsoft Corp. | Simultaneous localization and RF modeling |
CN105120517A (zh) * | 2015-07-29 | 2015-12-02 | 重庆邮电大学 | 基于多维尺度分析的室内wlan信号平面图构建与定位方法 |
WO2016079656A1 (en) * | 2014-11-18 | 2016-05-26 | Egypt-Japan University Of Science And Technology | Zero-calibration accurate rf-based localization system for realistic environments |
-
2017
- 2017-08-28 CN CN201710750288.8A patent/CN107396322B/zh active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8077090B1 (en) * | 2010-06-15 | 2011-12-13 | Microsoft Corp. | Simultaneous localization and RF modeling |
WO2016079656A1 (en) * | 2014-11-18 | 2016-05-26 | Egypt-Japan University Of Science And Technology | Zero-calibration accurate rf-based localization system for realistic environments |
CN105120517A (zh) * | 2015-07-29 | 2015-12-02 | 重庆邮电大学 | 基于多维尺度分析的室内wlan信号平面图构建与定位方法 |
Non-Patent Citations (3)
Title |
---|
JIANG LONG LIU ; YI HE WAN ; BAO GEN XU;SI LONG TANG: "A novel indoor positioning method based on location fingerprinting", 《2013 INTERNATIONAL CONFERENCE ON COMMUNICATIONS》 * |
郑文翰: "基于WLAN的室内定位技术研究与实现", 《中国优秀硕士学位论文全文数据库》 * |
龚阳;崔琛;余剑;孙从易;: "基于RBF神经网络的室内定位算法研究", 《电子测量技术》 * |
Cited By (28)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108399201A (zh) * | 2018-01-30 | 2018-08-14 | 武汉大学 | 一种基于循环神经网络的Web用户访问路径预测方法 |
CN108399201B (zh) * | 2018-01-30 | 2020-05-12 | 武汉大学 | 一种基于循环神经网络的Web用户访问路径预测方法 |
CN108957502B (zh) * | 2018-06-04 | 2022-10-21 | 安徽理工大学 | 基于深度学习lstm的gnss多***多路径误差实时削弱方法 |
CN108957502A (zh) * | 2018-06-04 | 2018-12-07 | 安徽理工大学 | 基于深度学习lstm的gnss多***多路径误差实时削弱方法 |
CN108629978A (zh) * | 2018-06-07 | 2018-10-09 | 重庆邮电大学 | 一种基于高维路网和循环神经网络的交通轨迹预测方法 |
CN108629978B (zh) * | 2018-06-07 | 2020-12-22 | 重庆邮电大学 | 一种基于高维路网和循环神经网络的交通轨迹预测方法 |
CN108984904A (zh) * | 2018-07-17 | 2018-12-11 | 北京理工大学 | 一种基于深度神经网络的家居设计方法 |
CN108984904B (zh) * | 2018-07-17 | 2022-09-20 | 北京理工大学 | 一种基于深度神经网络的家居设计方法 |
CN112930484B (zh) * | 2018-10-31 | 2024-05-28 | 三菱电机株式会社 | 定位***、定位方法和存储介质 |
CN112930484A (zh) * | 2018-10-31 | 2021-06-08 | 三菱电机株式会社 | 定位***、定位方法和存储介质 |
CN111372182A (zh) * | 2018-12-06 | 2020-07-03 | ***通信集团陕西有限公司 | 一种定位方法、装置、设备及计算机可读存储介质 |
CN109620154A (zh) * | 2018-12-21 | 2019-04-16 | 平安科技(深圳)有限公司 | 基于深度学习的肠鸣音识别方法及相关装置 |
CN110174690A (zh) * | 2019-05-30 | 2019-08-27 | 杭州中科微电子有限公司 | 一种基于长短期记忆网络辅助的卫星定位方法 |
CN110334741A (zh) * | 2019-06-06 | 2019-10-15 | 西安电子科技大学 | 基于循环神经网络的雷达一维距离像识别方法 |
CN110290466A (zh) * | 2019-06-14 | 2019-09-27 | ***通信集团黑龙江有限公司 | 楼层判别方法、装置、设备及计算机存储介质 |
EP3764120A1 (en) * | 2019-07-10 | 2021-01-13 | Swisscom AG | Low power wide area network localization |
US11782120B2 (en) | 2019-07-10 | 2023-10-10 | Swisscom Ag | Methods and systems for low power wide area network localization |
CN110533166A (zh) * | 2019-08-21 | 2019-12-03 | 中山大学 | 一种基于时空间融合特征的室内定位方法 |
CN110533166B (zh) * | 2019-08-21 | 2023-04-28 | 中山大学 | 一种基于时空间融合特征的室内定位方法 |
CN110519693B (zh) * | 2019-09-29 | 2020-11-03 | 东北大学 | 一种面向智能移动终端的融合定位方法 |
CN110519693A (zh) * | 2019-09-29 | 2019-11-29 | 东北大学 | 一种面向智能移动终端的融合定位方法 |
CN113051976A (zh) * | 2019-12-27 | 2021-06-29 | 广东博智林机器人有限公司 | 指纹定位方法、装置、电子设备及存储介质 |
CN114631365A (zh) * | 2020-01-02 | 2022-06-14 | 三星电子株式会社 | 检测位置的电子装置及其方法 |
CN112994840A (zh) * | 2021-02-03 | 2021-06-18 | 白盒子(上海)微电子科技有限公司 | 一种基于神经网络的译码器 |
CN112994840B (zh) * | 2021-02-03 | 2021-11-02 | 白盒子(上海)微电子科技有限公司 | 一种基于神经网络的译码器 |
CN113347559A (zh) * | 2021-05-14 | 2021-09-03 | 武汉大学 | 一种基于深度学习的强鲁棒性无线定位方法 |
CN113347559B (zh) * | 2021-05-14 | 2022-04-29 | 武汉大学 | 一种基于深度学习的强鲁棒性无线定位方法 |
CN114510044A (zh) * | 2022-01-25 | 2022-05-17 | 北京圣威特科技有限公司 | Agv导航船导航方法、装置、电子设备及存储介质 |
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