A Bioinspired Navigation System for Multirotor UAV by Integrating Polarization Compass/Magnetometer/INS/GNSS

Wang, Shanpeng; Qiu, Zhenbing; Huang, Panpan; Yu, Xiang; Jian, Yang; Guo, Lei

doi:10.1109/tie.2022.3212421

Cited by 11 publications

(5 citation statements)

References 32 publications

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“…Therefore, the Y-axis and Zaxis output signals of the geomagnetic sensor will mask the pitch and yaw angle information in the frequency domain, only displaying the roll angle velocity information of the HSA-UAV. According to the mathematical relationship between angular velocity and rotational speed, the relationship between HSA-UAV roll angle velocity and spin speed is shown in equation (9),…”

Section: The Output-signal Analysis Of Geomagnetic Sensorsmentioning

confidence: 99%

“…So far, the commonly used measurement elements for measuring the roll angle of high-speed flight carriers (HSFCs) are the combination of global navigation satellite system (GNSS) [1][2][3], MEMS inertial navigation systems [4][5][6] (MEMS-INSs), and geomagnetic sensors [7,8]. Among them, using geomagnetic sensors to measure the roll angle has the advantages of high reliability, low cost, no accumulated error, and passive autonomy, and can be used normally under satellite rejection conditions, it has been widely used in the field of navigation [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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A novel method for measuring roll angle

Zhang,

Gao,

Wang

et al. 2024

Meas. Sci. Technol.

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The precise measurement of the spin speed of a high-speed autonomous unmanned aerial vehicle (HAS-UAV) is a key element in mastering flight stability, and the measurement of roll angle is the key to determining the accuracy of navigation control systems. We put forward a novel method for measuring roll angle. This method starts from the time-frequency domain analysis (TFDA) of the output signal of the geomagnetic sensor, extracts the time-frequency ridge of the time-frequency matrix (TFM) to obtain the spin speed of the HSA-UAV, and reconstructs the output signal of the geomagnetic sensor. It can calculate the roll angle when the calibration parameters of the geomagnetic sensor are unknown and have good engineering practical value. In addition, we also propose an improved nonlinear short-time Fourier transform (INLSTFT) with high-frequency resolution and a forward penalty dynamic path ridge-extraction method (FPDPRM) with frequency jump suppression to extract instantaneous frequency (IF) in the TFM.

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Section: The Output-signal Analysis Of Geomagnetic Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel method for measuring roll angle

Zhang,

Gao,

Wang

et al. 2024

Meas. Sci. Technol.

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“…This approach contributes to enhancing the precision of the entire navigation system. When passing through a tunnel, although the

signal is blocked and the

information is inaccurate, the attitude information in the TMR digital compass is accurate and can continue to provide attitude correction for the

[ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ].…”

Section: Design Of High-precision Portable Digital Compass Systemmentioning

confidence: 99%

Development and Application of a High-Precision Portable Digital Compass System for Improving Combined Navigation Performance

Zhang,

Cui,

Zhang

2024

Sensors

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There are not many high-precision, portable digital compass solutions available right now that can enhance combined navigation systems’ overall functionality. Additionally, there is a dearth of writing about these products. This is why a tunnel magnetoresistance (TMR) sensor-based high-precision portable digital compass system is designed. First, the least-squares method is used to compensate for compass inaccuracy once the ellipsoid fitting method has corrected manufacturing and installation errors in the digital compass system. Second, the digital compass’s direction angle data is utilized to offset the combined navigation system’s mistake. The final objective is to create a high-performing portable TMR digital compass system that will enhance the accuracy and stability of the combined navigation system (abbreviated as CNS). According to the experimental results, the digital compass’s azimuth accuracy was 4.1824° before error compensation and 0.4580° after it was applied. The combined navigation system’s path is now more accurate overall and is closer to the reference route than it was before the digital compass was added. Furthermore, compared to the combined navigation route without the digital compass, the combined navigation route with the digital compass included is more stable while traveling through the tunnel. It is evident that the digital compass system’s design can raise the integrated navigation system’s accuracy and stability. The integrated navigation system’s overall performance may be somewhat enhanced by this approach.

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“…Inspiration from neuroscience is a promising approach for designing artificial visual systems with requirement of a high level of efficiency and robustness but limited in computational and memory budget [25]- [30]. It has attracted a great deal of interests and become an emerging research area with a number of practical applications, such as visually guided flights or landing [31], [32], autonomous navigation [33], [34], and collision detection [35], [36]. Our work is mainly related to two types of widely investigated motion-sensitive neurons, called lobula plate tangential cells (LPTCs) [37], [38] and small target motion detectors (STMDs), whose biological properties and computational models are briefly discussed.…”

Section: A Bio-inspired Motion Detectionmentioning

confidence: 99%

Bio-Inspired Small Target Motion Detection With Spatio-Temporal Feedback in Natural Scenes

Wang,

Zhong,

Lei

et al. 2024

IEEE Trans. on Image Process.

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Small moving objects at far distance always occupy only one or a few pixels in image and exhibit extremely limited visual features, which bring great challenges to motion detection. Highly evolved visual systems endow flying insects with remarkable ability to pursue tiny mates and prey, providing a good template to develop image processing method for small target motion detection. The insects' excellent sensitivity to small moving objects is believed to come from a class of specific neurons called small target motion detectors (STMDs). However, existing STMD-based methods often experience performance degradation when coping with complex natural scenes. In this paper, we propose a bio-inspired visual system with spatio-temporal feedback mechanism (called Spatio-Temporal Feedback STMD) to suppress false positive background movement while enhancing system responses to small targets. Specifically, the proposed visual system is composed of two complementary subnetworks and a feedback loop. The first subnetwork is designed to extract spatial and temporal movement patterns of cluttered background by neuronal ensemble coding. The second subnetwork is developed to capture small target motion information where its output and signal from the first subnetwork are integrated together via the feedback loop to filter out background false positives in a recurrent manner. Experimental results demonstrate that the proposed spatio-temporal feedback visual system is more competitive than existing methods in discriminating small moving targets from complex natural environments.

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A Bioinspired Navigation System for Multirotor UAV by Integrating Polarization Compass/Magnetometer/INS/GNSS

Cited by 11 publications

References 32 publications

A novel method for measuring roll angle

A novel method for measuring roll angle

Development and Application of a High-Precision Portable Digital Compass System for Improving Combined Navigation Performance

Bio-Inspired Small Target Motion Detection With Spatio-Temporal Feedback in Natural Scenes

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