A Hybrid Motion Compensation Scheme for THz-SAR with Composite Modulated Waveform.
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| Title: | A Hybrid Motion Compensation Scheme for THz-SAR with Composite Modulated Waveform. |
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| Authors: | Wu, Chongzheng1 (AUTHOR), Shi, Yanpeng1,2 (AUTHOR), Zhang, Xijian1 (AUTHOR), Zhang, Yifei1,2 (AUTHOR) yifeizhang@sdu.edu.cn |
| Source: | Remote Sensing. Dec2025, Vol. 17 Issue 24, p4036. 28p. |
| Subjects: | Motion compensation (Signal processing), High resolution imaging, Mechanical vibration research, Electronic modulation, Submillimeter wave imaging, Signal separation, Mathematical optimization |
| Abstract: | Highlights: What are the main findings? This work proposes a hybrid motion compensation scheme that simultaneously addresses non-stationary platform vibrations and trajectory deviations, overcoming the limitations of conventional methods that treated them individually. The proposed method achieves high-precision azimuth resolution across a range of SNR conditions, demonstrating superior performance compared to reported techniques. What is the implication of the main finding? It provides a robust and practical solution for high-resolution THz-SAR imaging, paving the way for vibration suppression in scenarios where platform motion is complex and non-stationary. The integrated approach of adaptive filtering, advanced signal decomposition, and hybrid optimization establishes a new benchmark for motion-error suppression in advanced radar systems. Terahertz Synthetic Aperture Radar (THz-SAR) is highly sensitive to platform vibrations and trajectory deviations, which introduce severe phase errors and limited resolution. Typically, platform vibrations and trajectory deviations are investigated individually, and vibrations are modeled as a stationary sine term. In this work, a hybrid motion compensation (MOCO) scheme is proposed to address both platform vibrations and trajectory deviations simultaneously, achieving improved imaging quality. The scheme initiates with a parameter self-adaptive quadratic Kalman filter designed to resolve severe phase wrapping. Then, platform vibration is modeled as a non-stationary multi-sine term, whose components are accurately extracted using an improved signal decomposition algorithm enhanced by a dynamic noise adjustment mechanism. Subsequently, the trajectory deviation is parameterized following subaperture division, estimated using a hybrid optimizer that combines particle swarm optimization and gradient descent. Additionally, a composite modulated waveform application ensures low sidelobes and a low probability of intercept (LPI). Extensive simulations on point targets and complex scenes under various signal-to-noise-ratio (SNR) conditions are applied for SAR image reconstruction, demonstrating robust suppression of motion errors. Under identical simulated error conditions, the proposed method achieves an azimuth resolution of 4.28 cm, which demonstrates superior performance compared to the reported MOCO techniques. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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