scholarly journals The Right Invariant Nonlinear Complementary Filter for Low Cost Attitude and Heading Estimation of Platforms

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Oscar De Silva ◽  
George K. I. Mann ◽  
Raymond G. Gosine
Keyword(s):  
Low Cost ◽  
Extended Kalman Filtering ◽  
Efficient Operation ◽  
Nonlinear Observers ◽  
System Noise ◽  
Computational Overhead ◽  
Complementary Filter ◽  
Aerial Vehicle ◽  
Heading Estimation ◽  
The Right

This paper presents a novel filter with low computational demand to address the problem of orientation estimation of a robotic platform. This is conventionally addressed by extended Kalman filtering (EKF) of measurements from a sensor suit which mainly includes accelerometers, gyroscopes, and a digital compass. Low cost robotic platforms demand simpler and computationally more efficient methods to address this filtering problem. Hence, nonlinear observers with constant gains have emerged to assume this role. The nonlinear complementary filter (NCF) is a popular choice in this domain which does not require covariance matrix propagation and associated computational overhead in its filtering algorithm. However, the gain tuning procedure of the complementary filter is not optimal, where it is often hand picked by trial and error. This process is counter intuitive to system noise based tuning capability offered by a stochastic filter like the Kalman filter. This paper proposes the right invariant formulation of the complementary filter, which preserves Kalman like system noise based gain tuning capability for the filter. The resulting filter exhibits efficient operation in elementary embedded hardware, intuitive system noise based gain tuning capability and accurate attitude estimation. The performance of the filter is validated using numerical simulations and by experimentally implementing the filter on an ARDrone 2.0 micro aerial vehicle (MAV) platform.

scholarly journals Enhanced Drone Navigation in GNSS Denied Environment Using VDM and Hall Effect Sensor

2019 ◽  
Vol 8 (4) ◽  
pp. 169 ◽  
Author(s):  
Shady Zahran ◽  
Adel Moussa ◽  
Naser El-Sheimy
Keyword(s):  
Hall Effect ◽  
Low Cost ◽  
Integrated System ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
Hall Effect Sensor ◽  
Aerial Vehicle ◽  
Heading Estimation ◽  
Global Navigation Satellite ◽  
Vehicle Dynamic Model

The last decade has witnessed a wide spread of small drones in many civil and military applications. With the massive advancement in the manufacture of small and lightweight Inertial Navigation System (INS), navigation in challenging environments became feasible. Navigation of these small drones mainly depends on the integration of Global Navigation Satellite Systems (GNSS) and INS. However, the navigation performance of these small drones deteriorates quickly when the GNSS signals are lost, due to accumulated errors of the low-cost INS that is typically used in these drones. During GNSS signal outages, another aiding sensor is required to bound the drift exhibited by the INS. Before adding any additional sensor on-board the drones, there are some limitations that must be taken into considerations. These limitations include limited availability of power, space, weight, and size. This paper presents a novel unconventional method, to enhance the navigation of autonomous drones in GNSS denied environment, through a new utilization of hall effect sensor to act as flying odometer “Air-Odo” and vehicle dynamic model (VDM) for heading estimation. The proposed approach enhances the navigational solution by estimating the unmanned aerial vehicle (UAV) velocity, and heading and fusing these measurements in the Extended Kalman Filter (EKF) of the integrated system.

scholarly journals Improved Attitude and Heading Accuracy with Double Quaternion Parameters Estimation and Magnetic Disturbance Rejection

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5475
Author(s):  
Assefinew Wondosen ◽  
Jin-Seok Jeong ◽  
Seung-Ki Kim ◽  
Yisak Debele ◽  
Beom-Soo Kang
Keyword(s):  
Attitude Determination ◽  
Low Cost ◽  
Experimental Tests ◽  
External Noise ◽  
Parameters Estimation ◽  
Magnetic Disturbance ◽  
Error Covariance ◽  
Aerial Vehicle ◽  
Heading Estimation ◽  
The Impact

The use of unmanned aerial vehicle (UAV) applications has grown rapidly over the past decade with the introduction of low-cost microelectromechanical system (MEMS)-based sensors that measure angular velocity, gravity, and magnetic field, which are important for an object orientation determination. However, the use of low-cost sensors has also been limited because their readings are easily distorted by unwanted internal and/or external noise signals such as environmental magnetic disturbance, which lead to errors in attitude and heading estimation results. In an extended Kalman filter (EKF) process, this study proposes a method for mitigating the effect of magnetic disturbance on attitude determination by using a double quaternion parameters for representation of orientation states, which decouples the magnetometer from attitude computation. Additionally, an online measurement error covariance matrix tuning system was implemented to reject the impact of magnetic disturbance on the heading estimation. Simulation and experimental tests were conducted to verify the performance of the proposed methods in resolving the magnetic noise effect on attitude and heading. The results showed that the proposed method performed better than complimentary, gradient descent, and single quaternion-based EKF.

Sensor Fusion for Attitude and Bias Estimation for a VTOL UAV

2010 ◽  
Author(s):  
Najib A. Metni
Keyword(s):  
Inertial Measurement Unit ◽  
Low Cost ◽  
Measurement Unit ◽  
Bias Estimation ◽  
Inertial Measurement ◽  
Complementary Filter ◽  
Vtol Uav ◽  
Orientation Matrix ◽  
Local Parametrization ◽  
Aerial Vehicle

In this paper, a nonlinear complementary filter is presented to estimate the attitude of a Vertical Take Off and Landing Unmanned Aerial Vehicle (VTOL UAV). The measurements are taken from a low-cost IMU (Inertial Measurement Unit) which consists of 3-axis accelerometers, 3-axis gyroscopes and 3-axis magnetometers. From the proposed estimators, the full orientation matrix R will be retrieved. The proposed observers will estimate the instantaneous quaternions as well as the gyroscope bias. This representation of orientation by the rotation matrix and quaternions allows overcoming the problem of singularities that appear in local parametrization such as Euler angles. Therefore, both estimators may be used to describe any kind of 3-D motion. Convergence of the two observers is theoretically proved and simulations are conducted taking data from a real platform in hovering flight conditions.

A Fast Adaptive-Gain Complementary Filter Algorithm for Attitude Estimation of an Unmanned Aerial Vehicle

2018 ◽  
Vol 71 (6) ◽  
pp. 1478-1491 ◽  
Author(s):  
Qing-quan Yang ◽  
Ling-ling Sun ◽  
Longzhao Yang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Estimation ◽  
Operating Conditions ◽  
Performance Ratio ◽  
Accelerometer Data ◽  
Extended Kalman Filtering ◽  
Simple Method ◽  
Discrete Dynamic System ◽  
Complementary Filter ◽  
Aerial Vehicle

A novel fast adaptive-gain complementary filter algorithm is developed for Unmanned Aerial Vehicle (UAV) attitude estimation. This approach provides an accurate, robust and simple method for attitude estimation with minimised attitude errors and reduced computation. UAV attitude data retrieved from accelerometer data is transformed to the solution of a linearly discrete dynamic system. A novel complementary filter is designed to fuse accelerometer and gyroscope data, with a self-adjusted gain to achieve a good performance in accuracy. The performance of the proposed algorithm is compared with an Adaptive-gain Complementary Filter (ACF) and Extended Kalman Filtering (EKF). Simulation and experimental results show that the accuracy of the proposed filter has the same performance as an EKF in high dynamic operating conditions. Therefore, the proposed algorithm can balance accuracy and time consumption, and it has a better price/performance ratio in engineering applications.

scholarly journals A Novel Electrically Small Ground-Penetrating Radar Patch Antenna with a Parasitic Ring for Respiration Detection

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1930
Author(s):  
Di Shi ◽  
Taimur Aftab ◽  
Gunnar Gidion ◽  
Fatma Sayed ◽  
Leonhard M. Reindl
Keyword(s):  
Ground Penetrating Radar ◽  
Patch Antenna ◽  
Low Cost ◽  
Substrate Material ◽  
Geometric Parameters ◽  
Gas Explosions ◽  
Aerial Vehicle ◽  
Electromagnetic Characteristics ◽  
Ground Penetrating ◽  
Quick Search

An electrically small patch antenna with a low-cost high-permittivity ceramic substrate material for use in a ground-penetrating radar is proposed in this work. The antenna is based on a commercial ceramic 915 MHz patch antenna with a size of 25 × 25 × 4 mm3 and a weight of 12.9 g. The influences of the main geometric parameters on the antenna’s electromagnetic characteristics were comprehensively studied. Three bandwidth improvement techniques were sequentially applied to optimize the antenna: tuning the key geometric parameters, adding cuts on the edges, and adding parasitic radiators. The designed antenna operates at around 1.3 GHz and has more than 40 MHz continuous −3 dB bandwidth. In comparison to the original antenna, the −3 and −6 dB fractional bandwidth is improved by 1.8 times and 4 times, respectively. Two antennas of the proposed design together with a customized radar were installed on an unmanned aerial vehicle (UAV) for a quick search for survivors after earthquakes or gas explosions without exposing the rescue staff to the uncertain dangers of moving on the debris.

Voice In Ear

2021 ◽  
Vol 5 (1) ◽  
pp. 1-25
Author(s):  
Yang Gao ◽  
Yincheng Jin ◽  
Jagmohan Chauhan ◽  
Seokmin Choi ◽  
Jiyang Li ◽  
...  
Keyword(s):  
User Authentication ◽  
Low Cost ◽  
The Body ◽  
Ear Canal ◽  
Replay Attacks ◽  
Increasing Demand ◽  
The Right ◽  
Sound Conduction ◽  
Enrollment Data ◽  
Secure Authentication

With the rapid growth of wearable computing and increasing demand for mobile authentication scenarios, voiceprint-based authentication has become one of the prevalent technologies and has already presented tremendous potentials to the public. However, it is vulnerable to voice spoofing attacks (e.g., replay attacks and synthetic voice attacks). To address this threat, we propose a new biometric authentication approach, named EarPrint, which aims to extend voiceprint and build a hidden and secure user authentication scheme on earphones. EarPrint builds on the speaking-induced body sound transmission from the throat to the ear canal, i.e., different users will have different body sound conduction patterns on both sides of ears. As the first exploratory study, extensive experiments on 23 subjects show the EarPrint is robust against ambient noises and body motions. EarPrint achieves an Equal Error Rate (EER) of 3.64% with 75 seconds enrollment data. We also evaluate the resilience of EarPrint against replay attacks. A major contribution of EarPrint is that it leverages two-level uniqueness, including the body sound conduction from the throat to the ear canal and the body asymmetry between the left and the right ears, taking advantage of earphones' paring form-factor. Compared with other mobile and wearable biometric modalities, EarPrint is a low-cost, accurate, and secure authentication solution for earphone users.

scholarly journals Patients in intensive care unit for COVID-19 pneumonia: the lung ultrasound patterns at admission and discharge. An observational pilot study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Persona Paolo ◽  
Valeri Ilaria ◽  
Zarantonello Francesco ◽  
Forin Edoardo ◽  
Sella Nicolò ◽  
...  
Keyword(s):  
Intensive Care ◽  
Lung Ultrasound ◽  
Low Cost ◽  
Low Frequency ◽  
Specific Pattern ◽  
University Hospital ◽  
Left Hemithorax ◽  
Significant Difference ◽  
The Right ◽  
B Lines

Abstract Background During COVID-19 pandemic, optimization of the diagnostic resources is essential. Lung Ultrasound (LUS) is a rapid, easy-to-perform, low cost tool which allows bedside investigation of patients with COVID-19 pneumonia. We aimed to investigate the typical ultrasound patterns of COVID-19 pneumonia and their evolution at different stages of the disease. Methods We performed LUS in twenty-eight consecutive COVID-19 patients at both admission to and discharge from one of the Padua University Hospital Intensive Care Units (ICU). LUS was performed using a low frequency probe on six different areas per each hemithorax. A specific pattern for each area was assigned, depending on the prevalence of A-lines (A), non-coalescent B-lines (B1), coalescent B-lines (B2), consolidations (C). A LUS score (LUSS) was calculated after assigning to each area a defined pattern. Results Out of 28 patients, 18 survived, were stabilized and then referred to other units. The prevalence of C pattern was 58.9% on admission and 61.3% at discharge. Type B2 (19.3%) and B1 (6.5%) patterns were found in 25.8% of the videos recorded on admission and 27.1% (17.3% B2; 9.8% B1) on discharge. The A pattern was prevalent in the anterosuperior regions and was present in 15.2% of videos on admission and 11.6% at discharge. The median LUSS on admission was 27.5 [21–32.25], while on discharge was 31 [17.5–32.75] and 30.5 [27–32.75] in respectively survived and non-survived patients. On admission the median LUSS was equally distributed on the right hemithorax (13; 10.75–16) and the left hemithorax (15; 10.75–17). Conclusions LUS collected in COVID-19 patients with acute respiratory failure at ICU admission and discharge appears to be characterized by predominantly lateral and posterior non-translobar C pattern and B2 pattern. The calculated LUSS remained elevated at discharge without significant difference from admission in both groups of survived and non-survived patients.

scholarly journals Whispering Gallery Mode Based Optical Fiber Sensor for Measuring Concentration of Salt Solution

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
Chia-Chin Chiang ◽  
Jian-Cin Chao
Keyword(s):  
Optical Fiber ◽  
Mass Production ◽  
Low Cost ◽  
Optical Fiber Sensor ◽  
Whispering Gallery Mode ◽  
Solution Concentration ◽  
Fiber Sensor ◽  
Average Sensitivity ◽  
Whispering Gallery ◽  
The Right

An optical fiber solution-concentration sensor based on whispering gallery mode (WGM) is proposed in this paper. The WGM solution-concentration sensors were used to measure salt solutions, in which the concentrations ranged from 1% to 25% and the wavelength drifted from the left to the right. The experimental results showed an average sensitivity of approximately 0.372 nm/% and anR2linearity of 0.8835. The proposed WGM sensors are of low cost, feasible for mass production, and durable for solution-concentration sensing.

scholarly journals Tracking the Evolution of Riverbed Morphology on the Basis of UAV Photogrammetry

2021 ◽  
Vol 13 (4) ◽  
pp. 829
Author(s):  
Teresa Gracchi ◽  
Guglielmo Rossi ◽  
Carlo Tacconi Stefanelli ◽  
Luca Tanteri ◽  
Rolando Pozzani ◽  
...  
Keyword(s):  
Management Practices ◽  
Low Cost ◽  
3D Models ◽  
Vegetation Coverage ◽  
Detection Analysis ◽  
Digital Terrain ◽  
Fluvial Dynamics ◽  
Aerial Vehicle ◽  
One Year ◽  
Short Time

Unmanned aerial vehicle (UAV) photogrammetry has recently become a widespread technique to investigate and monitor the evolution of different types of natural processes. Fluvial geomorphology is one of such fields of application where UAV potentially assumes a key role, since it allows for overcoming the intrinsic limits of satellite and airborne-based optical imagery on one side, and in situ traditional investigations on the other. The main purpose of this paper was to obtain extensive products (digital terrain models (DTMs), orthophotos, and 3D models) in a short time, with low costs and at a high resolution, in order to verify the capability of this technique to analyze the active geomorphic processes on a 12 km long stretch of the French–Italian Roia River at both large and small scales. Two surveys, one year apart from each other, were carried out over the study area and a change detection analysis was performed on the basis of the comparison of the obtained DTMs to point out and characterize both the possible morphologic variations related to fluvial dynamics and modifications in vegetation coverage. The results highlight how the understanding of different fluvial processes may be improved by appropriately exploiting UAV-based products, which can thus represent a low-cost and non-invasive tool to crucially support decisionmakers involved in land management practices.

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