Principles of Guidance, Navigation, and Control of UAVs

Communications, navigation, and other related systems need to have a well-defined antenna radiation pattern. In onboard vessel systems, the radiation pattern can be much different than the one obtained for an isolated antenna (because of the vessel’s structure and other nearby radiating systems interference). Finding out the onboard antenna’s radiation pattern is a well-known problem for any shipbuilder/owner. The conventional method consists of measuring radiation patterns from a fixed antenna on the coast while the ship is navigating in circles. Recent electronic systems in the market now allow for an alternative method: keeping the ship static while an unmanned aerial vehicle (UAV) circles it, measuring the antenna’s transmitted power. This research paper examines the airspace volume and optimal flight path of an off-the-shelf UAV system for measuring the onboard antenna’s radiation pattern in the presence of physical constraints such as the vessel’s dimensions, safety zone, distance to base, Fresnel’s and multipath distances, and considering the loss due to polarization decoupling between the antenna under test and UAV’s antenna.

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“…UAV flight guidance has been studied in [ 13 ]. In [ 14 ], a proportional guidance algorithm specific to circular flight path is implemented.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the operating conditions for UAV-based on-board antenna radiation pattern measurement systems

Núñez¹,

Orgeira-Crespo

Ulloa

et al. 2021

PLoS ONE

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“…Many studies presented the problem of the missing measurements (uncertainties) as a linear error; in other words, some predictable bias or constant offset affects equally all the measurements conducted under a given condition. 31 Due to the fact that most of the random vibration noise has nonlinear behavior, the external and internal uncertainties of complex technical systems (including UAVs) can be represented by a stochastic nonlinear differential equation with structural uncertainty 32…”

Section: Dynamic Parameter Identification Of Uavmentioning

confidence: 99%

Optimal control and state estimation for unmanned aerial vehicle under random vibration and uncertainty

Аl-Мashhadani

2019

Measurement and Control

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In the past decade, many approaches that attempted to solve the problem of optimal control and parameter estimation of an unmanned aerial vehicle with a priori uncertain parameters simply implied two ways to solve such problem. First, by the formation of optimal control based on a refined mathematical model of the unmanned aerial vehicle, and second, by using the estimation and identification methods of the model parameter of the unmanned aerial vehicle based on measured data from flight tests. However, the identification of the dynamic parameters of the unmanned aerial vehicle is a complicated task because of a number of factors such as random vibration noise, disturbance, and uncertainty of the sensor measurements. Due to the influence of random vibration noise, the problem of correlated vibration noises and uncertainty has encountered inevitably, and the accuracy of the state estimation for unmanned aerial vehicle is degraded. This study concentrates on the optimal control and state estimation for the unmanned aerial vehicle under the combination of both random vibration noise and uncertainty collected by the sensors. The effects of random vibrations at various stages of a large-scale flight that are a priori uncertain require the inclusion of identification algorithms in the optimal control loop. The results showed that the method used in the analysis had been able to provide accurate estimations.

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“…Navigation of Unmanned Aerial Vehicles (UAV) in the outdoor environment is mostly performed using the Global Navigation Satellite Systems (GNSS), and especially using the Global Positioning System (GPS) [1][2][3]. Despite the proper capability of GPS, this system is prone to some problems.…”

Section: Introductionmentioning

confidence: 99%

Spoofing Detection of Civilian UAVs Using Visual Odometry

Varshosaz

Afary

Mojaradi

et al. 2019

IJGI

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Spoofing of Unmanned Aerial Vehicles (UAV) is generally carried out through spoofing of the UAV’s Global Positioning System (GPS) receiver. This paper presents a vision-based UAV spoofing detection method that utilizes Visual Odometry (VO). This method is independent of the other complementary sensors and any knowledge or archived map and datasets. The proposed method is based on the comparison of relative sub-trajectory of the UAV from VO, with its absolute replica from GPS within a moving window along the flight path. The comparison is done using three dissimilarity measures including (1) Sum of Euclidian Distances between Corresponding Points (SEDCP), (2) angle distance and (3) taxicab distance between the Histogram of Oriented Displacements (HOD) of these sub-trajectories. This method can determine the time and location of UAV spoofing and bounds the drift error of VO. It can be used without any restriction in the usage environment and can be implemented in real-time applications. This method is evaluated on four UAV spoofing scenarios. The results indicate that this method is effective in the detection of UAV spoofing due to the Sophisticated Receiver-Based (SRB) GPS spoofing. This method can detect UAV spoofing in the long-range UAV flights when the changes in UAV flight direction is larger than 3° and in the incremental UAV spoofing with the redirection rate of 1°. Additionally, using SEDCP, the spoofing of the UAV, when there is no redirection and only the velocity of the UAV is changed, can be detected. The results show that SEDCP is more effective in the detection of UAV spoofing and fake GPS positions.

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Principles of Guidance, Navigation, and Control of UAVs

Cited by 37 publications

References 11 publications

Analysis of the operating conditions for UAV-based on-board antenna radiation pattern measurement systems

Analysis of the operating conditions for UAV-based on-board antenna radiation pattern measurement systems

Optimal control and state estimation for unmanned aerial vehicle under random vibration and uncertainty

Spoofing Detection of Civilian UAVs Using Visual Odometry

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