OFDM Radar Range Accuracy Enhancement Using Fractional Fourier Transformation and Phase Analysis Techniques

Li, Jianguo; An, Sining; An, Jianping; Zirath, Herbert; He, Zhongxia Simon

doi:10.1109/jsen.2019.2946003

Cited by 7 publications

(7 citation statements)

References 24 publications

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“…According to [22], the method of increasing the number of IFFT points can be adopted to improve the ranging accuracy. By introducing the fractional factor m a , the estimation function using fractional Fourier transform (FRFT) is…”

Section: A Range Estimation Using Prsmentioning

confidence: 99%

“…The fractional factor increases more search steps. Due to the fine accuracy of the estimation curve, the ranging accuracy is improved [22]. However, the ranging accuracy will only approach CRLB with infinitely increasing m a .…”

Section: A Range Estimation Using Prsmentioning

confidence: 99%

“…2) The Crámer-Rao lower bound (CRLB) of the range and velocity estimation concerning the PRS based sensing is derived, and the method of increasing the number of Fourier transform points [22] is applied to improve the accuracy of range and velocity estimation. In addition, an approach of velocity measurement using multiple frames is proposed to improve the accuracy of velocity estimation and reduce the time slot overhead within a frame.…”

Section: Introductionmentioning

confidence: 99%

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5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System

Wei

Wang

et al. 2023

IEEE Trans. Veh. Technol.

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The emerging joint sensing and communication (JSC) technology is expected to support new applications and services, such as autonomous driving and extended reality (XR), in the future wireless communication systems. Pilot (or reference) signals in wireless communications usually have good passive detection performance, strong anti-noise capability and good auto-correlation characteristics, hence they bear the potential for applying in radar sensing. In this paper, we investigate how to apply the positioning reference signal (PRS) of the 5th generation (5G) mobile communications in radar sensing. This approach has the unique benefit of compatibility with the most advanced mobile communication system available so far. Thus, the PRS can be regarded as a sensing reference signal to simultaneously realize the functions of radar sensing, communication and positioning in a convenient manner. Firstly, we propose a PRS based radar sensing scheme and analyze its range and velocity estimation performance, based on which we propose a method that improves the accuracy of velocity estimation by using multiple frames. Furthermore, the Crámer-Rao lower bound (CRLB) of the range and velocity estimation for PRS based radar sensing and the CRLB of the range estimation for PRS based positioning are derived. Our analysis and simulation results demonstrate the feasibility and superiority of PRS over other pilot signals in radar sensing. Finally, some suggestions for the future 5G-Advanced and 6th generation (6G) frame structure design containing the sensing reference signal are derived based on our study.

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Section: A Range Estimation Using Prsmentioning

confidence: 99%

Section: A Range Estimation Using Prsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System

Wei

Wang

et al. 2023

IEEE Trans. Veh. Technol.

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“…In order to reduce the quantization error, Li et al applied fractional Fourier transform (FRFT) to 2D FFT method, proposing 2D FRFT method. The 2D FRFT method increases the number of the points of Fourier transform, so that the quantization error is reduced and the sensing accuracy is improved [22]. However, the computational complexity in [22] is high.…”

Section: B Related Workmentioning

confidence: 99%

Iterative Signal Processing for Integrated Sensing and Communication Systems

Wei

Jiang

et al. 2023

IEEE Trans. on Green Commun. Netw.

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Integrated sensing and communication (ISAC), with sensing and communication sharing the same wireless resources and hardware, has the advantages of high spectrum efficiency and low hardware cost, which is regarded as one of the key technologies of the fifth generation advanced (5G-A) and sixth generation (6G) mobile communication systems. ISAC has the potential to be applied in the intelligent applications requiring both communication and high accurate sensing capabilities. The fundamental challenges of ISAC system are the ISAC signal design and ISAC signal processing. However, the existing ISAC signal has low anti-noise capability. And the existing ISAC signal processing algorithms have the disadvantages of quantization errors and high complexity, resulting in large energy consumption. In this paper, phase coding is applied in ISAC signal design to improve the anti-noise performance of ISAC signal. Then, the effect of phase coding method on improving the sensing accuracy is analyzed. In order to improve the sensing accuracy with low-complexity algorithm, the iterative ISAC signal processing methods are proposed. The proposed methods improve the sensing accuracy with low computational complexity, realizing energy efficient ISAC signal processing. Taking the scenarios of short distance and long distance sensing into account, the iterative two-dimensional (2D) fast Fourier transform (FFT) and iterative cyclic cross-correlation (CC) methods are proposed, respectively, realizing high sensing accuracy and low computational complexity. Finally, the feasibility of the proposed ISAC signal processing methods are verified by simulation results.

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“…In essence, fractional Fourier transform (FRFT) is a rotation operator in time–frequency signal processing characterised by an FRFT angle parameter

α

, which is the angle between the fractional Fourier domain and the time domain. Unlike the complex exponential‐based decomposition with Fourier transform, the FRFT utilising the chirp harmonic signals for decomposition has found application ranging from quantum mechanics, and radar accuracy enhancement [9] to optical and underwater acoustic (UWA) communications [10]. Recently, the performance of the FRFT‐based OFDM system is also specifically evaluated for applications like anti‐eavesdropping over multipath channel [11] and interference suppression for the Internet of Things (IoT) application [12].…”

Section: Introductionmentioning

confidence: 99%