Opportunities and Limitations in Radar Sensing Based on 5G Broadband Cellular Networks

Płotka, Marek; Abratkiewicz, Karol; Maksymiuk, Radosław; Wszołek, Jacek; Samczyński, Piotr; Zieliński, Tomasz P.

doi:10.1109/maes.2023.3267061

Cited by 6 publications

(3 citation statements)

References 26 publications

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“…5G: Kanhere conducted a simulation analysis on the method of using 5G signals for target localization and evaluated the performance of applying 5G in radar systems [6]. Księ żyk et al provided a detailed introduction to the basic principles of 5G sensing and conducted concept validation, explaining the feasibility and limitations of using 5G signals for passive radar and providing guidance for further research on passive radar based on 5G [7]. Abratkiewicz et al also studied the use of Synchronization Signaling Block (SSB) signals for target detection in addition to classical passive radar signal processing methods, and validated this method with cars as experimental targets, providing a new approach for target detection [8].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Rotating Target Detection Using Commercial 5G Signal

Chen,

Tian,

Bai

et al. 2024

Applied Sciences

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Passive radar detection emerges as a pivotal method for environmental perception and target detection within radar applications. Through leveraging its advantages, including minimal electromagnetic pollution and efficient spectrum utilization, passive radar methodologies have garnered increasing interest. In recent years, there has been an increasing selection of passive radar signal sources, and the emerging 5G has the characteristics of a high-frequency band, high bandwidth, and a large number of base stations, which give it significant advantages for use in passive radar. Therefore, in this paper, we introduce a passive radar target detection method based on 5G signals and design a rotating target speed measurement experiment. In the experiment, this paper validated the method of detecting rotating targets using 5G signals and evaluated the measurement accuracy, providing a research foundation for passive radar target detection using 5G signals and detecting rotating targets such as drone rotors.

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Section: Related Workmentioning

confidence: 99%

“…Additionally, the bandwidth and carrier frequency of communication signals are gradually increasing, which will improve the detection performance of passive radar, indicating the direction for its development. The rapidly developing 5G is also being applied to passive radar [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Rotating Target Detection Using Commercial 5G Signal

Chen,

Tian,

Bai

et al. 2024

Applied Sciences

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“…Radar systems have been playing a crucial role for object detection, data collection and telecommunication in diverse sectors encompassing from commercial uses and academic researches to military purposes [1], [2], [3], [4], [5], [6]. The wide applicability and technological reliability can be attributed to the nature resilient to hostile weather conditions and the well-established theoretical background [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Cross-Domain Translation Learning Method Utilizing Autoencoder Pre-Training for Super-Resolution of Radar Sparse Sensor Arrays

Kim

Hong

2023

IEEE Access

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This study proposes a convolutional neural network based image translation framework to faithfully realize the super-resolution of radar sensor sparse measurement. We exploited the Autoencoder model able to learn a latent representation of input domain data via the iteration of encoding and decoding processes. Based on the belief that the low resolution data retains an essential measurement to fully represent the sparse information of the high resolution counterpart, we assumed that input (source domain of low-resolution denoted by X ) and output (target domain of high-resolution denoted by Y ) share a common latent code. On the other hand, from the observation that the recovery quality of Y -to-Y translation is far more favorable than the outcome from X -to-Y translation, we performed the pre-training for finding the latent code (z y ) of the Y domain data, and subsequently the acquired z y serving as a label for predicting the latent code (z x ) of X domain data. As a result, in our proposed network, encoder and decoder parts were trained with separate minimization strategies relative to respective loss functions. For the sake of verifying the effect of the pre-training scheme, we introduced hyper-parameters, α and β, to regulate the training rate for the encoder and decoder parts respectively. As metrics for quantitative assessment, detection rate (DR), false alarm rate (FAR) and ROC curve were utilized. Our network set with 0.9 of α and 0.1 of β showed a higher ROC curve plot across the whole range of DR and FAR than a basic Autoencoder. DRs of the proposed network and comparative model were respectively 92.23% and 91.00% at FAR of 2%.

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5G‐based passive radar on a moving platform—Detection and imaging

Maksymiuk,

Gomez del Hoyo,

Abratkiewicz

et al. 2024

IET Radar Sonar & Navi

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In recent times, the development of radar systems for automotive applications has gathered significant interest due to the increasing necessity of vehicle situational awareness for new active protection systems and the intensive development of higher autonomous level driving solutions. Therefore, the number of active radars in automotive applications is growing, causing spectrum sharing and interference between radars operating in the same band. Alternative solutions without dedicated electromagnetic transmissions, such as joint communication and radar systems, or even no transmission at all, such as passive radars, have emerged in recent years and are promising solutions to help mitigate the interference problem. A passive automotive radar based on 5G communication signals is proposed as an alternative to active radars to provide situational awareness. The data downlink transmissions provided by an operative 5G base station were combined with a dual‐channel passive radar (PR) system deployed on a moving platform to provide moving target detection and radar imaging of the vehicle's surroundings. The outcomes show a possibility of commensal utilisation of the new telecommunication standard for automotive radar applications. The idea of mounting the PR receiver on a moving platform was tested using simulated and real‐life data, which shows great potential for joining the new radio (NR) with sensing capabilities using PR. The theory, numerical experiments, and measurement results are dealt with a cooperative 5G base station and PR demonstrator.

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Opportunities and Limitations in Radar Sensing Based on 5G Broadband Cellular Networks

Cited by 6 publications

References 26 publications

Rotating Target Detection Using Commercial 5G Signal

Rotating Target Detection Using Commercial 5G Signal

Cross-Domain Translation Learning Method Utilizing Autoencoder Pre-Training for Super-Resolution of Radar Sparse Sensor Arrays

5G‐based passive radar on a moving platform—Detection and imaging

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