Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

Kong, Bo; Wang, Yuhao; Leung, Henry; Deng, Xiaohua; Zhou, Huilin; Zhou, Fuhui

doi:10.1155/2017/6528956

Cited by 4 publications

(4 citation statements)

References 36 publications

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“…In order to implement a processor for the estimation of delay and Doppler frequency, the transmitted information has to be removed from the surveillance channel firstly. In OFDM-based passive radar, the reference signal includes a direct path signal and multipath signals, and the clean reference signal can be obtained by reconstruction [25]. Therefore, the transmitted signal…”

Section: Mth Nthmentioning

confidence: 99%

Coarse-Fine Joint Target Parameter Estimation Method Based on AN-RSC in OFDM Passive Radar

Wang,

Wan,

et al. 2024

J. of Syst. Eng. Electron.

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In this paper, we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing (OFDM) signal. A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational burden. Firstly, the modulation symbol domain (MSD) method is used to roughly estimate the delay and Doppler of targets. Then, to obtain high-precision Doppler estimation, the atomic norm (AN) based on the multiple measurement vectors (MMV) model (MMV-AN) is used to manifest the signal sparsity in the continuous Doppler domain. At the same time, a reference signal compensation (RSC) method is presented to obtain highprecision delay estimation. Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other algorithms. In addition, the proposed method also possesses computational advantages compared with the joint parameter estimation.

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Section: Mth Nthmentioning

confidence: 99%

Coarse-Fine Joint Target Parameter Estimation Method Based on AN-RSC in OFDM Passive Radar

Wang,

Wan,

et al. 2024

J. of Syst. Eng. Electron.

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“…ExtractÛ to get E 1R , E 2R , E 1v , and E 2v in Equations ( 39) and (40) 45) and (46), then perform diagonalisation on them 5. Calculate the range and velocity of the targets in Equations ( 47) and ( 48 17. Find the maximum value and record R k , v k 18.…”

Section: Algorithm 1 the E-w Algorithmmentioning

confidence: 99%

“…A two‐stage method for multi‐target range and velocity estimation based on OFDM passive radar is proposed in [16], requiring multiple receivers. A modulation symbol‐domain method combined with sparse representation (SR) for range‐Doppler estimation is introduced in [17]. However, its random subcarrier allocation mechanism reduces the communication rate.…”

Section: Introductionmentioning

confidence: 99%

Joint range and velocity estimation for integration of radar and communication based on multi‐symbol OFDM radar pulses

Wang

Zhang

Najafabadi

2021

IET Radar Sonar & Navi

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Integration of radar and communication (IRC) is conducive to improving hardware resource utilization and spectrum utilization. This paper proposes a joint range and velocity estimation method for IRC based on multi-symbol orthogonal frequency division multiplexing (OFDM) radar pulses. A two-step parameters estimation method is applied, where estimating the signal parameters via rotational invariance technique (ESPRIT) and weighted subspace fitting (WSF) perform rough and fine estimations. We first build a receiving model for integrated signal based on element-wise division. The ESPRIT method is then adopted based on the double Vandermonde structure array manifold for a rough estimation. It has relatively high estimation error but low computational complexity. The WSF method based on alternating projection (AP) algorithm is introduced to make the estimation more precise and reduce its error. It uses the estimation results in the first step and reduces the overall computational cost. Simulation results show that the proposed method reduces the computational complexity while improving the estimation accuracy compared with the WSF method.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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“…Although in radio frequency (RF) front-end architectures, both the radar and communication become similar, operating radar and communication simultaneously cause a series of problems such as the number of antennas, the energy consumption, and electromagnetic signal interference. So the concept of joint radar-communication (JRC) is proposed in the recent few decades, which enables radar and wireless communication users working in the same frequency band, sharing the same antenna resources, implementing radar sensing, and communication transmission synchronously [3][4][5][6][7][8]. A typical JRC is illustrated in Figure 1, it is shown that the JRC signal is sent from the radar transmitter, and the communication and radar are operated simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Joint Radar-Communication Relying on Spread Spectrum: A Hybrid Chaotic Sequence Design

Wang

Sun

et al. 2020

Wireless Communications and Mobile Computing

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This paper investigates a novel design for joint radar-communication (JRC) waveform, which is capable of improving the network’s performance by solving the phase shift mutation of the Chirp-BPSK waveform. We aim for jointly designing chirp waveform and improving Binary Phase Shift Keying (BPSK), as well as the hybrid chaotic spread spectrum code (CSSC). As a benefit, the JRC waveform can be successfully decoded, and the accumulation of phase shift can be suppressed by hybrid CSSC. The detailed deduction on the short-time Fourier transform (STFT) of the JRC waveform is adopted to analyse the complicated AF characters. Our analytical results demonstrate that the proposed JRC signal has superior spectrum performance, ambiguity function (AF), and transmission rate than conventional Chirp and Chirp-BPSK waveform. Numerical results are provided to confirm that (i) the proposed waveform is capable of providing better communication and radar performance; (ii) the performance of AF is not affected by the transmission rate for the proposed waveform.

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Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

Cited by 4 publications

References 36 publications

Coarse-Fine Joint Target Parameter Estimation Method Based on AN-RSC in OFDM Passive Radar

Coarse-Fine Joint Target Parameter Estimation Method Based on AN-RSC in OFDM Passive Radar

Joint range and velocity estimation for integration of radar and communication based on multi‐symbol OFDM radar pulses

Joint Radar-Communication Relying on Spread Spectrum: A Hybrid Chaotic Sequence Design

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