公开(公告)号：US20210041548A1

公开(公告)日：2021-02-11

申请号：US16988204

申请日：2020-08-07

申请人： Biao Chen ,  Yang Liu ,  Tiexing Wang

发明人： Biao Chen ,  Yang Liu ,  Tiexing Wang

IPC分类号： G01S13/00 ,  G01S13/56 ,  G01S7/41

摘要： A system for using radio frequency (RF) communication signals to extract situational awareness information thorough deep learning. Pre-processing is performed to maximally preserve discriminating features in spatial, temporal and frequency domains. A specially designed neural network architecture is used for handling complex RF signals and extracting spatial, temporal and frequency domain information. Data collection and training is used so that the learning system desensitizes from features orthogonal to the underlying classification problem.

公开(公告)号：US11125553B2

公开(公告)日：2021-09-21

申请号：US15631046

申请日：2017-06-23

申请人： Biao Chen ,  Tiexing Wang ,  Fangrong Peng

发明人： Biao Chen ,  Tiexing Wang ,  Fangrong Peng

IPC分类号： G01B17/00 ,  G01S15/08 ,  G01S15/89 ,  G01S15/06

摘要： Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile device 10 by collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.

公开(公告)号：US20170370710A1

公开(公告)日：2017-12-28

申请号：US15631046

申请日：2017-06-23

申请人： Biao Chen ,  Tiexing Wang ,  Fangrong Peng

发明人： Biao Chen ,  Tiexing Wang ,  Fangrong Peng

IPC分类号： G01B17/00 ,  G01S15/89 ,  G01S15/08

CPC分类号： G01B17/00 ,  G01B17/06 ,  G01S15/06 ,  G01S15/08 ,  G01S15/89

摘要： Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile device 10 by collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.