A Trajectory Estimation Method Based on Microwave Three-Point Ranging for Sparse 3D Radar Imaging

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Publicado en:Remote Sensing vol. 17, no. 20 (2025), p. 3397-3419
Autor Principal: Lou Changyu
Outros autores: Zhao Jingcheng, Wu, Xingli, Yang Zongkai, Miao Jungang, Hong, Tao
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MDPI AG
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024 7 |a 10.3390/rs17203397  |2 doi 
035 |a 3265942341 
045 2 |b d20250101  |b d20251231 
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100 1 |a Lou Changyu 
245 1 |a A Trajectory Estimation Method Based on Microwave Three-Point Ranging for Sparse 3D Radar Imaging 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a <sec sec-type="highlights"> What are the main findings? <list list-type="bullet"> <list-item> A microwave three-point ranging scheme with three external reflective spheres uniquely determines the radar’s 3D position at each sample—even under random jitter—without any communications link. </list-item> <list-item> The resulting trajectory accuracy enables high-fidelity 3D radar imaging under sparse sampling. </list-item> What is the implication of the main finding? <list list-type="bullet"> <list-item> A simple, retrofit-friendly external calibration (three spheres) increases the robustness and flexibility of sparse near-field radar imaging. </list-item> <list-item> The method scales to UAV-borne 3D imaging, supporting accurate in-flight radar localization without relying on communications. </list-item> Precise estimate of antenna location is essential for high-quality three-dimensional (3D) radar imaging, especially under sparse sampling schemes. In scenarios involving synchronized scanning and rotational motion, small deviations in the radar’s transmitting position can lead to significant phase errors, thereby degrading image fidelity or even causing image failure. To address this challenge, we propose a novel trajectory estimation method based on microwave three-point ranging. The method utilizes three fixed microwave-reflective calibration spheres positioned outside the imaging scene. By measuring the one-dimensional radial distances between the radar and each of the three spheres, and geometrically constructing three intersecting spheres in space, the radar’s spatial position can be uniquely determined at each sampling moment. This external reference-based localization scheme significantly reduces positioning errors without requiring precise synchronization control between scanning and rotation. Furthermore, the proposed approach enhances the robustness and flexibility of sparse sampling strategies in near-field radar imaging. Beyond ground-based setups, the method also holds promise for drone-borne 3D imaging applications, enabling accurate localization of onboard radar systems during flight. Simulation results and error analysis demonstrate that the proposed method improves trajectory accuracy and supports high-fidelity 3D reconstruction under non-ideal sampling conditions. 
653 |a Spheres 
653 |a Accuracy 
653 |a Scanning 
653 |a Radar 
653 |a Calibration 
653 |a Radar imaging 
653 |a Synchronization 
653 |a Image degradation 
653 |a Unmanned aerial vehicles 
653 |a Synchronism 
653 |a Error analysis 
653 |a Flight 
653 |a Localization 
653 |a Sampling 
653 |a Robustness 
653 |a Global positioning systems--GPS 
653 |a Image reconstruction 
653 |a Trajectories 
653 |a Radar equipment 
653 |a Near fields 
653 |a Onboard equipment 
653 |a Flexibility 
653 |a Retrofitting 
653 |a Drones 
653 |a Three dimensional imaging 
653 |a Error reduction 
700 1 |a Zhao Jingcheng 
700 1 |a Wu, Xingli 
700 1 |a Yang Zongkai 
700 1 |a Miao Jungang 
700 1 |a Hong, Tao 
773 0 |t Remote Sensing  |g vol. 17, no. 20 (2025), p. 3397-3419 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3265942341/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3265942341/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3265942341/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch