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Physics-Inspired Target Shape Detection and Reconstruction in mmWave Communication Systems

Ziqing Xing, Zhaoyang Zhang, Xin Tong, Zhaohui Yang, Chongwen Huang

TL;DR

The paper tackles shape sensing in mmWave ISAC by modeling mmWave propagation with ray tracing, including both reflection and Lambertian scattering on a single convex polygon. It introduces a two-stage point-detection pipeline (periodogram, CFAR, and MUSIC-based refinement) to extract scattering and reflection points, followed by HT-PCA-TSR for initial polygon fitting and a reflection-based refinement to improve completeness and accuracy. The approach demonstrates that fusing scattering and reflection information enhances shape reconstruction, especially at moderate to low SNR, as validated by extensive simulations in a multi-BS MIMO-OFDM setting. This work advances deterministic environment sensing for mmWave ISAC by integrating physical propagation models with robust geometric fitting and multi-view fusion, enabling more reliable target-shape reconstruction in realistic wireless sensing scenarios.

Abstract

The integration of sensing and communication (ISAC) is an essential function of future wireless systems. Due to its large available bandwidth, millimeter-wave (mmWave) ISAC systems are able to achieve high sensing accuracy. In this paper, we consider the multiple base-station (BS) collaborative sensing problem in a multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) mmWave communication system. Our aim is to sense a remote target shape with the collected signals which consist of both the reflection and scattering signals. We first characterize the mmWave's scattering and reflection effects based on the Lambertian scattering model. Then we apply the periodogram technique to obtain rough scattering point detection, and further incorporate the subspace method to achieve more precise scattering and reflection point detection. Based on these, a reconstruction algorithm based on Hough Transform and principal component analysis (PCA) is designed for a single convex polygon target scenario. To improve the accuracy and completeness of the reconstruction results, we propose a method to further fuse the scattering and reflection points. Extensive simulation results validate the effectiveness of the proposed algorithms.

Physics-Inspired Target Shape Detection and Reconstruction in mmWave Communication Systems

TL;DR

The paper tackles shape sensing in mmWave ISAC by modeling mmWave propagation with ray tracing, including both reflection and Lambertian scattering on a single convex polygon. It introduces a two-stage point-detection pipeline (periodogram, CFAR, and MUSIC-based refinement) to extract scattering and reflection points, followed by HT-PCA-TSR for initial polygon fitting and a reflection-based refinement to improve completeness and accuracy. The approach demonstrates that fusing scattering and reflection information enhances shape reconstruction, especially at moderate to low SNR, as validated by extensive simulations in a multi-BS MIMO-OFDM setting. This work advances deterministic environment sensing for mmWave ISAC by integrating physical propagation models with robust geometric fitting and multi-view fusion, enabling more reliable target-shape reconstruction in realistic wireless sensing scenarios.

Abstract

The integration of sensing and communication (ISAC) is an essential function of future wireless systems. Due to its large available bandwidth, millimeter-wave (mmWave) ISAC systems are able to achieve high sensing accuracy. In this paper, we consider the multiple base-station (BS) collaborative sensing problem in a multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) mmWave communication system. Our aim is to sense a remote target shape with the collected signals which consist of both the reflection and scattering signals. We first characterize the mmWave's scattering and reflection effects based on the Lambertian scattering model. Then we apply the periodogram technique to obtain rough scattering point detection, and further incorporate the subspace method to achieve more precise scattering and reflection point detection. Based on these, a reconstruction algorithm based on Hough Transform and principal component analysis (PCA) is designed for a single convex polygon target scenario. To improve the accuracy and completeness of the reconstruction results, we propose a method to further fuse the scattering and reflection points. Extensive simulation results validate the effectiveness of the proposed algorithms.
Paper Structure (12 sections, 23 equations, 7 figures, 1 table, 1 algorithm)

This paper contains 12 sections, 23 equations, 7 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Multi-BSs Sensing Scenario
  4. Signal Propagation and Channel Model
  5. Point Target Reconstruction
  6. Scattering Points Detection
  7. Reflection Points Detection
  8. Target Shape Reconstruction
  9. The HT-PCA-TSR Algorithm
  10. Target Shape Refinement
  11. Simulation Results
  12. Conclusions

Figures (7)

  • Figure 1: Considered multi-BS environment sensing scenario.
  • Figure 2: The reflection and scattering model of mmWaves.
  • Figure 3: Two cases of invalid line fitting.
  • Figure 4: The channel simulation and periodogram analysis.
  • Figure 5: Scattering and reflection points detection.
  • ...and 2 more figures