W Band Mini-SAR on Multi Rotor UAV Platform

Ding, Manlai; Tang, Lin; Zhou, Liangjiang; Wang, Xuemei; Weng, Zhilei; Qu, Jiameng

doi:10.1109/iceict.2019.8846356

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…Additionally, the CRLB for range measurements using the STLFMCW signal with a rectangular envelope is given as Eq. (27), illustrating that the CRLB of the proposed algorithm is determined by the swept bandwidth of the LFM waveform and the received SNR.…”

Section: Discusion Of the Proposed Algorithmmentioning

confidence: 99%

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

Wang

Xiang

et al. 2020

IEEE Access

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The combination of synthetic aperture radar (SAR) with unmanned aerial vehicles (UAVs) is attractive for acquiring high-resolution images without the restrictions of time and weather. However, because UAVs are lightweight and small in size, the UAV SAR system is very sensitive to turbulence, resulting in serious trajectory deviations and remaining residual motion errors (RMEs), such as residual range cell migration (RCM) and aperture phase errors (APEs). In this paper, a novel motion compensation (MoCo) strategy is developed based on the symmetric triangle linear frequency modulated continuous wave (STLFMCW) signal. The STLFMCW signal model is first presented, which reveals the relevance between the positive-negative frequency modulations and motion errors. The residual RCMs and relative phase errors are estimated directly through the phase differential interferometry of up-ramp and down-ramp chirp signals, instead of the traditional approach of relying on the range-shift gradient of adjacent range profiles. The proposed approach is independent of conventional prominent point processing (PPP) and calculates the range deviation to avoid the accumulation of errors, thereby achieving high precision and efficiency. Experiments based on simulated and measured data sets validate the proposed approach.

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Section: Discusion Of the Proposed Algorithmmentioning

confidence: 99%

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

Wang

Xiang

et al. 2020

IEEE Access

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“…In the control algorithm of multirotor UAVs, the most common methods are the PID control algorithm [11], sliding mode control algorithm [12][13][14], and robust control algorithms such as disturbance rejection control [6,15,16]. With the increasing complexity of multirotor UAVs [17][18][19][20], researchers have considered combining adaptive control technology with robust control technology to better control such complex systems [14]. To address the uncertain dynamic parameters and external disturbances in the system, Lu et al used neural networks to identify uncertain parameters in the system, which performed well in the control of such nonlinear systems [21].…”

Section: Introductionmentioning

confidence: 99%

Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

Hua,

Zhang,

et al. 2024

CMES

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With the increasing prevalence of high-order systems in engineering applications, these systems often exhibit significant disturbances and can be challenging to model accurately. As a result, the active disturbance rejection controller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmanned aerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances and the possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address these issues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neural network (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm. We integrate the plant protection UAV model's uncertain parameters, load disturbance parameters, and actuator fault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits load disturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law has Lyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platform demonstrate that the proposed method outperforms other control strategies regarding load disturbance suppression and fault-tolerant performance.

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“…Li [27] suggested an adaptive control scheme based on a fixed-time observer (FTOAC) for UAV tracking control. Additionally, there are numerous UAV design optimization studies utilizing intelligent algorithms [28,29]. Inspired by these studies, this paper introduces a commonality quantification evaluation method based on the UAV design structure matrix and a commonality prediction method based on convolutional neural networks.…”

Section: Introductionmentioning

confidence: 99%

Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs

Zhang,

Zeng,

Cao

2023

Drones

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Light small-sized, multi-rotor UAVs, with their notable advantages of portability, intelligence, and low cost, occupy a significant share in the civilian UAV market. To further reduce the full lifecycle cost of products, shorten development cycles, and increase market share, some manufacturers of these UAVs have adopted a series development strategy based on the concept of commonality in design. However, there is currently a lack of effective methods to quantify the commonality in UAV designs, which is key to guiding commonality design. In view of this, our study innovatively proposes a new UAV commonality evaluation model based on the basic composition of light small-sized multi-rotor UAVs and the theory of design structure matrices. Through cross-evaluations of four models, the model has been confirmed to comprehensively quantify the degree of commonality between models. To achieve commonality prediction in the early stages of multi-rotor UAV design, we constructed a commonality prediction dataset centered around the commonality evaluation model using data from typical light small-sized multi-rotor UAV models. After training this dataset with convolutional neural networks, we successfully developed an effective predictive model for the commonality of new light small-sized multi-rotor UAV models and verified the feasibility and effectiveness of this method through a case application in UAV design. The commonality evaluation and prediction models established in this study not only provide strong decision-making support for the series design and commonality design of UAV products but also offer new perspectives and tools for strategic development in this field.

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W Band Mini-SAR on Multi Rotor UAV Platform

Cited by 8 publications

References 6 publications

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

A Novel Motion Compensation Approach Based on Symmetric Triangle Wave Interferometry for UAV SAR Imagery

Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs

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