Cell-Free Integrated Sensing and Communication for UGV Detection Based on Decomposed Back Projection Algorithm

This paper considers the localization and velocimetry problem of UGV by integrated sensing and communications in a Sub-6GHz cell-free system. Multiple distributed antennas are used to detect a single target and the echo signals are processed. For the receiver processing algorithm, we develop an improved algorithm suitable for real systems to address the problem that the matched-filter based backprojection algorithm consumes too much time. By de-composing range and velocity, the original algorithm is split into range backprojection and velocity backprojection algorithms respectively, and the effective target is identified by constant alarm false rate (CFAR) algorithm. Simulation results show that the improved algorithm increased the computation speed by at least 100 times. For the real system, better results are achieved by proposed algorithm for localization and velocimetry as well.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icus61736.2024.10839755
Citations
1
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.21
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Cell-Free Integrated Sensing and Communication for UGV Detection Based on Decomposed Back Projection Algorithm

Zhiqiang Yue, Dongxuan He, Huazhou Hou, Yongming Huang
1 citations
Advanced MIMO Systems Optimization
0.21
article

Cell-Free Integrated Sensing and Communication for UGV Detection Based on Decomposed Back Projection Algorithm

Zhiqiang Yue, Dongxuan He, Huazhou Hou, Yongming Huang
article en
1 citations

Abstract

This paper considers the localization and velocimetry problem of UGV by integrated sensing and communications in a Sub-6GHz cell-free system. Multiple distributed antennas are used to detect a single target and the echo signals are processed. For the receiver processing algorithm, we develop an improved algorithm suitable for real systems to address the problem that the matched-filter based backprojection algorithm consumes too much time. By de-composing range and velocity, the original algorithm is split into range backprojection and velocity backprojection algorithms respectively, and the effective target is identified by constant alarm false rate (CFAR) algorithm. Simulation results show that the improved algorithm increased the computation speed by at least 100 times. For the real system, better results are achieved by proposed algorithm for localization and velocimetry as well.

Purple Mountain Laboratories (CN), Southeast University (CN)
Openalex Percentile: Top 44%
Advanced MIMO Systems Optimization
0.21
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