5G Based Localization

♦ Introduction and Background

The 5G based localization is getting more and more concerned from academia and industry thanks to the higher resolution of angle and distance estimation resulting from the larger bandwidth and larger amount of antennas. It was also exciting to find that the multiple path components in the radio propagation would actually enhance the performance of localization instead of performing as a noise. What’s more, the localization utilizing 5G radio signals also demonstrates higher level of stability with less cost. So we focus on the 5G based localization technologies especially in the context of autonomous driving, and here is what we have done.

♦ Equipment and Methods

The research team utilize two USRP devices as the transmitter and receiver to achieve indoor angle measurement. Based on AOA positioning method, the measurement angle can be used for positioning.

Figure 1 Experimental facilities

♦ Experimental Results

One antenna was used at the transmitter and two antennas were used at the receiver. The antenna spacing was 4.28cm, the carrier frequency was 3.5GHz, the transceiver spacing was 3-4m, and the measurement accuracy was within 5 degrees.

Figure 2 Experimental results

♦ Future Deployment

This technology will be deployed on OAI and used for positioning in underground tunnels in Xiong’an New Area.

Figure 3 Deployment scenarios

♦ Publications

  • Papers

[1] Xinghe Chu, Zhaoming Lu, David Gesbert, Luhan Wang, Xiangming Wen, Vehicle Localization via Cooperative Channel Mapping, 15 April 2021, IEEE Transactions on Vehicular Technology

[2] Xinghe Chu, Zhaoming Lu, Luhan Wang, Xiangming Wen, David Gesbert, Team Channel-SLAM: A Cooperative Mapping Approach to Vehicle Localization, 21 July 2020, IEEE ICC Workshop

[3] Xinghe Chu, Zhaoming Lu, Luhan Wang, Muqing Wu, Xiangming Wen, Multi-Path Assisted Cooperative Radio-Based Localization for Connected Vehicles, April 2021, Journal of Beijing University of Posts and Telecommunications

[4] Xinghe Chu, Zhaoming Lu, David Gesbert, et.al., Joint Vehicular Localization and Reflective Mapping Based on Team Channel-SLAM, IEEE Transactions on Wireless Communications (Under Review)

[5] Yuhao Ling, Xinghe Chu, Zhaoming Lu, Luhan Wang, Xiangming Wen, PCM: A Positioning Calibration Mechanism for Connected Autonomous Vehicles, May 2020, IEEE Access

[6] Wanyu Meng, Xinghe Chu, Zhaoming Lu, Luhan Wang, Xiangming Wen, Meiling Li, V2V Communication Assisted Cooperative Localization for Connected Vehicles, May 2021, IEEE WCNC

  • Patents
Granted
  • X.Chu, X.Wen, L.Wang, Z.Lu and X.Chen, “Automatic driving target classification method and system based on multi-sensor information fusion,”2021.4, ZL201810627515.2
  • Z.Lu, Y.Ling, X.Chu, L.Wang and X.Wen,“Network delay location error compensation method, device and electronic equipment,” 2021.2 ZL201910425384.4
  • Raymond Knopp, X.Chu, Z.Lu, L.Wang and L.Ma, “Power allocation among users in a downlink in non-orthogonal multiple access,” 2020.11 ZL201710719719.4
  • X.Wen, B.Zhu, Z.Lu, L.Wang, P.Lu, X.Ouyang and H.Zhang,“Multi-target tracking methods, devices, electronic devices and readable storage media“ 2021.7 CN202110506679.1
Filed
  • X.Wen, J.Deng, Z.Lu, L.Wang , P.Lu , X.Ouyang and H.Zhang,“Road inclination detection method and detection system,” 2021.6, CN202110461939.8
  • L.Wang D.Li X.Chu G.Wang B.Fu,“Positioning method, device and system of vehicle terminal in 5G connected autonomous driving” 2020.11, CN202011287479.3
  • Z.Lu, W.Meng, X.Chu, L.Wang and X.Wen,“:Acquisition method of arrival time and arrival Angle of multipath signal and related devices,”2021.5, CN202110553482.3
  • Z.Lu, T.Su, X.Chu, L.Wang, X.Wen and D.Li,“Measurement signal processing methods, devices, electronic equipment and readable storage media”2021.1, CN202011255283.6

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