High-Resolution Imaging Based on Coherent Processing for Distributed Multi-Band Radar Data

He, Feiyang; Xu, Xiaojian

doi:10.2528/pier13062504

Cited by 10 publications

(4 citation statements)

References 20 publications

(33 reference statements)

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“…Noncooperative target recognition has been a highly concerned issue in recent years, leading to modern radar performs target imaging and recognition tasks besides conventional tasks of detection and tracking [1][2][3]. High range resolution profile (HRRP) achieved by larger working bandwidth is considered as a promising technology for noncooperative target identification [4,5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Velocity Estimation and Compensation Approach for Moving Target in Stepped Frequency Radar Based on Fractional Fourier Transform

Peng,

Chen,

Zhang

et al. 2023

Preprint

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The Stepped Frequency Waveform (SFW) is commonly employed in radar technology to synthesize wideband signals through the aggregation of narrow-band pulses, thereby achieving high-resolution range profiles without the need to increase the radar's instantaneous bandwidth. However, the inherent large time-bandwidth product of SFW introduces substantial ranging errors and energy dispersion, which significantly hinders its efficacy in detecting high-speed objects. This paper introduces a pioneering velocity estimation technique utilizing the fractional Fourier transform (FrFT) to address these limitations. Leveraging the characteristic of the Doppler signal from a moving target, which manifests as a chirp signal with a rate proportional to the target's velocity, the FrFT is utilized for precise velocity estimation. Subsequent to this, velocity compensation is applied using the deduced metrics, followed by the application of the inverse fast Fourier transform (iFFT) to pinpoint the target's exact location. To optimize the computational efficiency of determining the FrFT's optimal order, we propose an iterative algorithm founded on the golden section search method. The effectiveness of the proposed approach is verified by simulation data, and the results demonstrate that the proposed approach can accurately estimate the velocity and the range of the high-speed targets with a relatively low computational complexity.

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Section: Introductionmentioning

confidence: 99%

A Novel Velocity Estimation and Compensation Approach for Moving Target in Stepped Frequency Radar Based on Fractional Fourier Transform

Peng,

Chen,

Zhang

et al. 2023

Preprint

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“…In addition to the above‐mentioned fusion methods, He [12] used a De‐noising Cross Correlation, or DNCC, algorithm to estimate the phase error between multi‐band signals. Then, he proposed to implement data fusion by two‐dimensional Gapped‐data State Space Approach, or 2‐D GS SA, which does not require overlap between sub‐frequency signals.…”

Section: Introductionmentioning

confidence: 99%

Multi‐subband fusion algorithm based on autoencoder

Jiang

Zhang

Li³

et al. 2022

IET Signal Processing

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A novel algorithm for multi-subband signal fusion achieves performance superior to traditional all-pole model, matrix pencil algorithm and deep-neural-network (Deep neural network (DNN)). The method uses a deep-learning autoencoder more fully described as a multi-subband fusion autoencoder (MSFAE). This autoencoder comprises two parts: a multi-subband encoder and a full-band decoder. Full-band echo distance envelopes are used as training data for the full-band autoencoder, to obtain the full-band coding and the full-band decoder. Then, the multi-subband echo distance envelopes are used as training data, and the full-band coding is used as labels, to train the multi-subband encoder. Finally, the multi-subband encoder and the full-band decoder are combined to obtain the MSFAE. The multi-subband distance envelopes are input to the MSFAE to obtain the full-band distance envelopes, improving the radar distance resolution and obtaining highresolution range profiles. In contrast with the traditional all-pole model and matrix pencil algorithm, the authors' MSFAE directly processes the information in the frequency domain, avoiding the error of pole estimation in the echo domain. In contrast with DNN, the authors' MSFAE needs only multi-subband distance envelopes as input, avoiding noise subband redundancy. The experimental results show that the fusion accuracy of MSFAE is higher than the traditional all-pole model, matrix pencil algorithm and DNN. The MSFAE has superior performance using the fusion method, even at low signal-to-noise ratio.

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“…In this process, we regard the beat signal with two different Doppler frequencies as a composition of two incoherent subbands. Lincoln laboratory has developed a mutual‐coherence processing approach for ultra‐wideband coherent processing [14, 15]. This approach can effectively solve the incoherence problem of the two subbands of the beat signal.…”

Section: Introductionmentioning

confidence: 99%

Long‐distance imaging with frequency modulation continuous wave and inverse synthetic aperture radar

Wen

Jin

et al. 2015

IET Radar, Sonar & Navigation

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High-Resolution Imaging Based on Coherent Processing for Distributed Multi-Band Radar Data

Cited by 10 publications

References 20 publications

A Novel Velocity Estimation and Compensation Approach for Moving Target in Stepped Frequency Radar Based on Fractional Fourier Transform

A Novel Velocity Estimation and Compensation Approach for Moving Target in Stepped Frequency Radar Based on Fractional Fourier Transform

Multi‐subband fusion algorithm based on autoencoder

Long‐distance imaging with frequency modulation continuous wave and inverse synthetic aperture radar

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