scholarly journals Low-cost Positioning and Heading Determination System: Experimental Classical 2D EKF Sensors Fusion and Accuracy Evaluation

2021 ◽  
Author(s):  
Adrian Kaczmarek ◽  
Witold Rohm ◽  
Lasse Klingbeil ◽  
Janusz Tchórzewski
Keyword(s):  
Low Cost ◽  
Accuracy Evaluation ◽  
Determination System ◽  
Sensors Fusion

A Novel GNSS Attitude Determination Method Based on Primary Baseline Switching for A Multi-Antenna Platform

2020 ◽  
Vol 12 (5) ◽  
pp. 747
Author(s):  
Peng Zhang ◽  
Yinzhi Zhao ◽  
Huan Lin ◽  
Jingui Zou ◽  
Xinzhe Wang ◽  
...  
Keyword(s):  
Attitude Determination ◽  
Low Cost ◽  
Satellite System ◽  
Poor Quality ◽  
Integrated Navigation ◽  
Determination Method ◽  
Integrated Navigation System ◽  
Determination System ◽  
Vehicle Test ◽  
Global Navigation Satellite

The global navigation satellite system (GNSS)-based attitude determination system has attracted more and more attention with the advantages of having simplified algorithms, a low price and errors that do not accumulate over time. However, GNSS signals may have poor quality or lose lock in some epochs with the influence of signal fading and the multipath effect. When the direct attitude determination method is applied, the primary baseline may not be available (ambiguity is not fixed), leading to the inability of attitude determination. With the gradual popularization of low-cost receivers, making full use of spatial redundancy information of multiple antennas brings new ideas to the GNSS-based attitude determination method. In this paper, an attitude angle conversion algorithm, selecting an arbitrary baseline as the primary baseline, is derived. A multi-antenna attitude determination method based on primary baseline switching is proposed, which is performed on a self-designed embedded software and hardware platform. The proposed method can increase the valid epoch proportion and attitude information. In the land vehicle test, reference results output from a high-accuracy integrated navigation system were used to evaluate the accuracy and reliability. The results indicate that the proposed method is correct and feasible. The valid epoch proportion is increased by 16.2%, which can effectively improve the availability of attitude determination. The RMS of the heading, pitch and roll angles are 0.52°, 1.25° and 1.16°.

scholarly journals Deeply Integrated GNSS/Gyro Attitude Determination System

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2203
Author(s):  
Alexander Perov ◽  
Alexander Shatilov
Keyword(s):  
Attitude Determination ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Dynamic Environment ◽  
Global Navigation Satellite Systems ◽  
Satellite Systems ◽  
System Sensitivity ◽  
Low Snr ◽  
Determination System ◽  
Phase Differences

Attitude determination systems based on Global Navigation Satellite Systems (GNSS) work on principle of phase interferometer, using multiple receiving antennas. They rely on a good quality of carrier phase tracking, that is not the case in real dynamic environment with low signal-to-noise ratio (SNR), for example, in a ground vehicle moving through an urban area or forest. There is still a problem in providing a GNSS attitude in such common conditions. This research is focused on improving sensitivity (i.e., the capability of providing attitude at a low SNR) and the reliability of the GNSS attitude determination system. It is contrasted with the majority of publications, where precision or computational efficiency is the main goal, but sensitivity and reliability are out of their scope. In the proposed system, sensitivity improved by using two measures: (a) tracking only phase differences instead of tracking full carrier phases—this is more sensitive due to the lower dynamics of the underlying process, and (b) using deep integration with gyroscope, where all phase differences are tracked in a vector gyro-aided loop closed on user’s attitude in state vector. The algorithm synthesis is given, and simulation results are presented in this article. This shows that the minimal working SNR is lowered from 27–36 dBHz (typical) down to 20 dBHz, even with a low-cost MEMS gyroscope.

scholarly journals A supervised machine learning semantic segmentation approach for detecting artifacts in plethysmography signals from wearables

2021 ◽  
Author(s):  
Zhicheng Guo ◽  
Cheng Ding ◽  
Xiao Hu ◽  
Cynthia Rudin
Keyword(s):  
Binary Classification ◽  
Low Cost ◽  
Semantic Segmentation ◽  
Poor Quality ◽  
Supervised Machine Learning ◽  
Accuracy Evaluation ◽  
Design Of Algorithms ◽  
Artifact Detection ◽  
Segmentation Approach ◽  
Testing Set

Abstract Objective. Wearable devices equipped with plethysmography (PPG) sensors provided a low-cost, long-term solution to early diagnosis and continuous screening of heart conditions. However PPG signals collected from such devices often suffer from corruption caused by artifacts. The objective of this study is to develop an effective supervised algorithm to locate the regions of artifacts within PPG signals. Approach. We treat artifact detection as a 1D segmentation problem. We solve it via a novel combination of an active-contour-based loss and an adapted U-Net architecture. The proposed algorithm was trained on the PPG DaLiA training set, and further evaluated on the PPG DaLiA testing set, WESAD dataset and TROIKA dataset. Main results. We evaluated with the DICE score, a well-established metric for segmentation accuracy evaluation in the field of computer vision. The proposed method outperforms baseline methods on all three datasets by a large margin (≈ 7 percentage points above the next best method). On the PPG DaLiA testing set, WESAD dataset and TROIKA dataset, the proposed method achieved 0.8734±0.0018, 0.9114±0.0033 and 0.8050±0.0116 respectively. The next best method only achieved 0.8068±0.0014, 0.8446±0.0013 and 0.7247±0.0050. Significance. The proposed method is able to pinpoint exact locations of artifacts with high precision; in the past, we had only a binary classification of whether a PPG signal has good or poor quality. This more nuanced information will be critical to further inform the design of algorithms to detect cardiac arrhythmia.

Rapid Low-Cost Moisture Determination System

1971 ◽  
Vol 54 (5) ◽  
pp. 1009-1010 ◽  
Author(s):  
M Solberg ◽  
W E Riha
Keyword(s):  
Low Cost ◽  
Infrared Heating ◽  
Moisture Determination ◽  
Oven Method ◽  
Fresh Meat ◽  
System A ◽  
Determination System

Abstract The Ohaus 770-moisture determination system, a rapid low-cost moisture-determining system based upon infrared heating, was evaluated. Several types of frankfurters and ground fresh meat were tested. The results obtained were comparable to those obtained by the official AOAC air oven method.

scholarly journals Low-Cost MEMS-Based Pedestrian Navigation Technique for GPS-Denied Areas

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Abdelrahman Ali ◽  
Naser El-Sheimy
Keyword(s):  
Low Cost ◽  
Pressure Sensors ◽  
Micro Electro Mechanical System ◽  
Attitude Estimation ◽  
Handheld Devices ◽  
Accelerometer Data ◽  
Pedestrian Navigation ◽  
Heading Estimation ◽  
Sensors Fusion ◽  
New Research

The progress in the micro electro mechanical system (MEMS) sensors technology in size, cost, weight, and power consumption allows for new research opportunities in the navigation field. Today, most of smartphones, tablets, and other handheld devices are fully packed with the required sensors for any navigation system such as GPS, gyroscope, accelerometer, magnetometer, and pressure sensors. For seamless navigation, the sensors’ signal quality and the sensors availability are major challenges. Heading estimation is a fundamental challenge in the GPS-denied environments; therefore, targeting accurate attitude estimation is considered significant contribution to the overall navigation error. For that end, this research targets an improved pedestrian navigation by developing sensors fusion technique to exploit the gyroscope, magnetometer, and accelerometer data for device attitude estimation in the different environments based on quaternion mechanization. Results indicate that the improvement in the traveled distance and the heading estimations is capable of reducing the overall position error to be less than 15 m in the harsh environments.

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