Non-Line-of-Sight Multi-Target Localization Algorithm for Driver-Assistance Radar System

Chen, Jiahui; Guo, Shisheng; Luo, Haolan; Li, Nian; Cui, Guolong

doi:10.1109/tvt.2022.3227971

Cited by 19 publications

(1 citation statement)

References 21 publications

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“…Numerous approaches for non-intrusive target detection and tracking based on various sensors already exist [4,5]. Millimeter-wave radar-based target tracking technology can locate and track targets by evaluating the reflected signal in the scene, and its highbandwidth and high-frequency band features enable the system to achieve high precision and high coverage.…”

Section: Introductionmentioning

confidence: 99%

A Robust Target Tracking Method for Crowded Indoor Environments Using mmWave Radar

et al. 2023

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Millimeter-wave-based extended target tracking has attracted extensive interest recently because of its privacy, high precision, and low cost. This paper concentrated on crowded indoor situations and presents a novel method for group tracking. First, the proposed alpha-extended Kalman filter and the group association were carried out, which can constantly estimate the target expansion and the number of reflection points, consequently modifying the measurement noise and covariance estimation. Then, to initialize the actual targets, we employed a density-based spatial clustering approach that includes false target suppression. After the targets have been updated, the track re-association and estimation procedure is conducted to account for the unanticipated break of moving and near-static targets. Finally, various experiments involving fewer than 11 participants were designed to assess the robustness of the method. As a result, continuous and steady tracking results, as well as high counting accuracy were obtained.

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Section: Introductionmentioning

confidence: 99%

A Robust Target Tracking Method for Crowded Indoor Environments Using mmWave Radar

et al. 2023

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Rotor unmanned aerial vehicle localization in the building sheltered area based on millimetre‐wave frequency‐modulated continuous wave radar

Zhang,

Zeng,

Yang

et al. 2024

IET Radar Sonar & Navi

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Rotor unmanned aerial vehicles (UAVs) play an important role in both military and civilian fields nowadays. The safety risks associated with the UAVs increase the urgent need for detecting UAVs in urban environments as well. Moreover, UAVs are easily located in the non‐line‐of‐sight (NLOS) building sheltered area relative to the radar, making it very challenging to detect and localise. A novel algorithm for localising the rotor UAV in the common L‐shaped street building sheltered area is proposed. First, the authors establish a multipath signal model for a rotor UAV hovering over an L‐shaped street scene, leveraging the frequency‐modulated continuous wave signal. Then, the multipath information of the UAV is extracted by identifying the rotating periodicity of the blade embedded in the time‐frequency spectrum of the received signal. The back projection imaging is then conducted on the UAV‐related multipath. After extracting multipath ghosts in the image, the street area, where the UAV locates, can be determined, and the UAV is further localised using the path reflection characteristics of this area. Simulations and practical experiments based on millimetre waves indicate that the proposed method can enable high‐accuracy estimation of rotor UAV in the NLOS building sheltered area.

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Cramer-Rao Performance Bounds for NLOS Target Localization Behind L-shaped Corner

Xu,

Guo,

Chen

et al. 2023

2023 9th International Conference on Computer and Communications (ICCC)

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Non-Line-of-Sight Multi-Target Localization Algorithm for Driver-Assistance Radar System

Cited by 19 publications

References 21 publications

A Robust Target Tracking Method for Crowded Indoor Environments Using mmWave Radar

A Robust Target Tracking Method for Crowded Indoor Environments Using mmWave Radar

Rotor unmanned aerial vehicle localization in the building sheltered area based on millimetre‐wave frequency‐modulated continuous wave radar

Cramer-Rao Performance Bounds for NLOS Target Localization Behind L-shaped Corner

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