High-Resolution Microwave Photonic Radar With Sparse Stepped Frequency Chirp Signals

Ma, Cong; Yue, Yang; Cao, Fengting; Wang, Xiangchuan; Xi, Liu; Meng, Chenkai; Zhang, Jiangtao; Pan, Shilong

doi:10.1109/tgrs.2022.3208112

Cited by 13 publications

(4 citation statements)

References 47 publications

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“…However, the coherent FMCW-based photonic radar is more complex and costly compared to direct detection FMCW-based photonic radar. In another work [22], the authors proposed a microwave photonic radar, which employs sparse stepped-frequency (SSF) chirp signals to achieve ultra-high resolution. The proposed photonic radar can distinguish two simulated point targets placed within the distance of 8.3 mm.…”

Section: Related Workmentioning

confidence: 99%

Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

Chaudhary,

Sharma,

Naeem

et al. 2024

Sustainability

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The rapid deployment of 5G autonomous vehicles has placed a premium on low-latency communication and reliable sensor technologies for the real-time mapping of road conditions, aligning with sustainability objectives in transport. In response to this imperative, photonic-based radar systems have emerged as an increasingly attractive solution, characterized by their low power consumption and cost-effectiveness. This study delves into the application of linear frequency-modulated continuous wave (FMCW) techniques within photonic radar sensors for the precise detection of multiple targets. Our proposed system seamlessly integrates mode-division multiplexing (MDM) and polarization-division multiplexing (PDM) to achieve a robust target detection capability, contributing to sustainable traffic management. To assess its effectiveness, we rigorously evaluated the system’s performance under challenging conditions, marked by a high atmospheric attenuation of 75 dB/km and a low material reflectivity of 20%. Our results unequivocally demonstrate the efficacy of the MDM-PDM photonic radar in successfully detecting all four specified targets, underscoring its potential to enhance road safety in the realm of autonomous vehicles. The adoption of this technology supports sustainable mobility by mitigating human errors and optimizing the real-time mapping of road conditions.

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Section: Related Workmentioning

confidence: 99%

Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

Chaudhary,

Sharma,

Naeem

et al. 2024

Sustainability

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show abstract

“…The results indicated that coherent detection-based photonic radar outperformed direct detection FMCW-based photonic radar, but it is more complex and costly. Another study [ 17 ] proposed microwave photonic radar that utilizes sparse stepped frequency (SSF) chirp signals to achieve ultra-high resolution. This photonic radar was able to distinguish between two simulated point targets placed 8.3 mm apart.…”

Section: Introductionmentioning

confidence: 99%

Highly efficient photonic radar by incorporating MDM-WDM and machine learning classifiers under adverse weather conditions

Chaudhary,

Sharma,

Singh

et al. 2024

PLoS ONE

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Photonic radar, a cornerstone in the innovative applications of microwave photonics, emerges as a pivotal technology for future Intelligent Transportation Systems (ITS). Offering enhanced accuracy and reliability, it stands at the forefront of target detection and recognition across varying weather conditions. Recent advancements have concentrated on augmenting radar performance through high-speed, wide-band signal processing–a direct benefit of modern photonics’ attributes such as EMI immunity, minimal transmission loss, and wide bandwidth. Our work introduces a cutting-edge photonic radar system that employs Frequency Modulated Continuous Wave (FMCW) signals, synergized with Mode Division and Wavelength Division Multiplexing (MDM-WDM). This fusion not only enhances target detection and recognition capabilities across diverse weather scenarios, including various intensities of fog and solar scintillations, but also demonstrates substantial resilience against solar noise. Furthermore, we have integrated machine learning techniques, including Decision Tree, Extremely Randomized Trees (ERT), and Random Forest classifiers, to substantially enhance target recognition accuracy. The results are telling: an accuracy of 91.51%, high sensitivity (91.47%), specificity (97.17%), and an F1 Score of 91.46%. These metrics underscore the efficacy of our approach in refining ITS radar systems, illustrating how advancements in microwave photonics can revolutionize traditional methodologies and systems.

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“…To address these limitations, microwave photonics (MWP), an emerging interdisciplinary field that integrates microwave and photonic technologies, presents a promising solution [3] . Leveraging the inherent advantages of photonics, such as wide bandwidth, low frequency-dependent loss, flexible tunability, and electromagnetic interference resilience, MWP has garnered significant attention and extensive research in radar signal generation over the past decade [4][5][6] . Nevertheless, the research on the FDA signal generation method based on MWP remains relatively limited.…”

Section: Introductionmentioning

confidence: 99%

Frequency diverse array signal generation based on dual optical frequency combs

Tan,

Zhong,

Wang

et al. 2023

AOPC 2023: AI in Optics and Photonics

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High-Resolution Microwave Photonic Radar With Sparse Stepped Frequency Chirp Signals

Cited by 13 publications

References 47 publications

Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

Target Detection in Challenging Environments: Photonic Radar with a Hybrid Multiplexing Scheme for 5G Autonomous Vehicles

Highly efficient photonic radar by incorporating MDM-WDM and machine learning classifiers under adverse weather conditions

Frequency diverse array signal generation based on dual optical frequency combs

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