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IEICE Transactions on Communications
Online ISSN : 1745-1345
Print ISSN : 0916-8516
Regular Section
Motion Parameter Estimation Based on Overlapping Elements for TDM-MIMO FMCW Radar
Feng TIANWan LIUWeibo FUXiaojun HUANG
Author information
  • Feng TIAN

    Xi'an University of Science and Technology

  • Wan LIU

    Xi'an University of Science and Technology

  • Weibo FU

    Xi'an University of Science and Technology

  • Xiaojun HUANG

    Xi'an University of Science and Technology

Corresponding author

ORCID
Keywords:millimeter wave radar,time division multiplexing multiple input multiple output (TDM MIMO),motion compensation,velocity ambiguity
JOURNALRESTRICTED ACCESS

2023 Volume E106.BIssue 8Pages 705-713

DOIhttps://doi.org/10.1587/transcom.2022EBP3088
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Details
  • Published: August 01, 2023Manuscript Received: May 23, 2022Released on J-STAGE: August 01, 2023Accepted: -Advance online publication: February 06, 2023Manuscript Revised: November 21, 2022
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Abstract

Intelligent traffic monitoring provides information support for autonomous driving, which is widely used in intelligent transportation systems (ITSs). A method for estimating vehicle moving target parameters based on millimeter-wave radars is proposed to solve the problem of low detection accuracy due to velocity ambiguity and Doppler-angle coupling in the process of traffic monitoring. First of all, a MIMO antenna array with overlapping elements is constructed by introducing them into the typical design of MIMO radar array antennas. The motion-induced phase errors are eliminated by the phase difference among the overlapping elements. Then, the position errors among them are corrected through an iterative method, and the angle of multiple targets is estimated. Finally, velocity disambiguation is performed by adopting the error-corrected phase difference among the overlapping elements. An accurate estimation of vehicle moving target angle and velocity is achieved. Through Monte Carlo simulation experiments, the angle error is 0.1° and the velocity error is 0.1m/s. The simulation results show that the method can be used to effectively solve the problems related to velocity ambiguity and Doppler-angle coupling, meanwhile the accuracy of velocity and angle estimation can be improved. An improved algorithm is tested on the vehicle datasets that are gathered in the forward direction of ordinary public scenes of a city. The experimental results further verify the feasibility of the method, which meets the real-time and accuracy requirements of ITSs on vehicle information monitoring.

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