Efficient Rotational Angular Velocity Estimation of Rotor Target via Modified Short-Time Fractional Fourier Transform

Wang, Wantian; Zhu, Yong; Tang, Ziyue; Chen, Yichang; Zhu, Zhenbo; Sun, Yongjian; Zhou, Chang

doi:10.3390/rs13101970

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…Multiple targets or components of the target have various micro-movements, such as the precession and nutation of warhead targets [5,6], the swing of sea surface ships [7], the rotation of tank tracks [8], the swing of human arms and legs [9], and the vibration of birds' wings during flight [10,11]. Rotorcraft targets are also an essential type of micro-motion targets [12,13], mainly referring to targets containing rotatable blade components, including helicopters, wind turbines, rotorcraft, multi-rotor drones, and propeller aircraft. Rotor targets can generate micro-Doppler effects and periodic micro-Doppler frequency bands through blade rotation.…”

Section: Introductionmentioning

confidence: 99%

Micro‐motion signal time‐frequency results inversion of rotor targets under low signal‐to‐noise ratios

Long,

Yang,

et al. 2024

IET Radar Sonar & Navi

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A signal time‐frequency results inversion method is proposed for extracting micro‐motion features of rotor targets under low signal‐to‐noise ratios (SNRs). In the case of low SNRs, the echo's energy of rotor targets is mainly concentrated in the flash's echo component. Conventional micro‐motion feature extraction of rotor targets primarily utilises the sinusoidal modulation feature in time‐frequency results, whose energy is much lower than the flash. Under low SNRs, the sinusoidal modulation in the echo's time‐frequency results will be submerged in the noise, making feature extraction challenging. A deep learning network is used to inverse the time‐frequency results containing sinusoidal modulation based on the flash's features in the time‐frequency results. Based on the inversion time‐frequency results, the GS‐IRadon algorithm is used to extract micro‐motion features, which can significantly reduce the times of IRadon transformations and improve feature extraction speed and accuracy. Through simulation and analysis, a novel method using a deep learning network like UNet can effectively inverse time‐frequency results under low SNRs, providing a new technical approach for micro‐motion feature extraction. Time‐frequency results inversion is a novelty method used to achieve micro‐motion feature extraction of rotor targets.

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Section: Introductionmentioning

confidence: 99%

Micro‐motion signal time‐frequency results inversion of rotor targets under low signal‐to‐noise ratios

Long,

Yang,

et al. 2024

IET Radar Sonar & Navi

View full text Add to dashboard Cite

show abstract

“…In many works, for example [34,35], the authors indicate that temperature shock can violate the orientation requirements. This is especially true of the requirements for the angular velocity of the small spacecraft rotation at the time of remote sensing of the Earth [36,37].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Perturbations Arising from Temperature Shock with a Symmetrical Arrangement of Flexible Elements of a Small Spacecraft

Bormotov

Orlov

2023

Symmetry

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This paper investigates the effect of a temperature shock on a small spacecraft with symmetrically arranged flexible elements. A two-dimensional thermoelasticity problem is posed. The disturbing effect of temperature shock on a small spacecraft has been determined. The assessment of the main disturbing factors arising from the temperature shock of flexible elements of a small spacecraft was carried out. Approximate dependences were obtained for the components of the displacement vector of the flexible element points. Numerical simulation was carried out for the symmetric scheme of the small spacecraft with two and four flexible elements. The dependence of the inertia force on temperature shock for the simulated small spacecraft at various initial deflections of the flexible element was constructed. Conclusions were drawn about the significance of the temperature shock influence on the dynamics of a small spacecraft. The results obtained were compared with the results of other studies and can be used in solving problems of remote sensing of the Earth and the implementation of gravity-sensitive processes on board small spacecraft.

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“…This method also had excellent robustness in a low-SNR environment. In 2021, Wang Wantian of the School of Early Warning proposed an effective method for estimating the rotational angular velocity of rotor targets based on the combination of a time-frequency analysis algorithm and the Hough transform [16]. This approach is effective in resolving issues with the short-time Fourier transform and Wigner-Ville distribution algorithms' poor time-frequency resolution and cross-term interference.…”

Section: Introductionmentioning

confidence: 99%

Micro-Doppler Feature Extraction of Rotating Structures of Aircraft Targets with Terahertz Radar

2022

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The micro-Doppler features formed by the micro-motion of rotating blades of rotors and turbines are of great significance for aircraft target detection and recognition. Mastering the micro-motion features is the premise of radar target identification. The blades’ length and rotation rate are vital parameters for classifying aircraft targets. One can instantly judge the type and state of the targets by extracting micro-Doppler features. To extract the micro-Doppler features of rotating blades of the turbine target, we utilized microwave-band and terahertz-band radar to simulate the target and extract the Doppler frequency-shift information. For a turbine model with an obvious blade tip structure, we propose an algorithm based on wavelet coefficient enhancement and inverse Radon transform, integrating the time–frequency analysis with image processing. Under low SNR, this method allows for a high-accuracy parameter estimate. For a two-bladed rotor model without an obvious blade tip structure, we conducted an actual measurement experiment on the model utilizing a 120 GHz radar, and we propose a parameter estimation algorithm based on the fitting of the time–frequency distribution. By fitting the data of the time–frequency diagram, the micro-motion characteristic parameters of the rotor target were obtained. The simulation and experimental results demonstrate the benefits of terahertz radar in target detection, and indicate that the proposed algorithms have the characteristics of high extraction precision and insensitivity to noise.

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Efficient Rotational Angular Velocity Estimation of Rotor Target via Modified Short-Time Fractional Fourier Transform

Cited by 5 publications

References 39 publications

Micro‐motion signal time‐frequency results inversion of rotor targets under low signal‐to‐noise ratios

Micro‐motion signal time‐frequency results inversion of rotor targets under low signal‐to‐noise ratios

Investigation of Perturbations Arising from Temperature Shock with a Symmetrical Arrangement of Flexible Elements of a Small Spacecraft

Micro-Doppler Feature Extraction of Rotating Structures of Aircraft Targets with Terahertz Radar

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