Research on velocity estimation in high dynamic flight simulation with a stand-alone single-frequency GPS receiver

2016 ◽  
Author(s):  
Feng Li ◽  
Qiang Li ◽  
Xudong Liu
Keyword(s):  
Flight Simulation ◽  
Velocity Estimation ◽  
Single Frequency ◽  
Gps Receiver ◽  
High Dynamic

scholarly journals High-precision coseismic displacement estimation with a single-frequency GPS receiver

2015 ◽  
Vol 202 (1) ◽  
pp. 612-623 ◽  
Author(s):  
Bofeng Guo ◽  
Xiaohong Zhang ◽  
Xiaodong Ren ◽  
Xingxing Li
Keyword(s):  
High Precision ◽  
Single Frequency ◽  
Gps Receiver ◽  
Coseismic Displacement ◽  
Displacement Estimation

Detection of Spoofing Attack using Machine Learning based on Multi-Layer Neural Network in Single-Frequency GPS Receivers

2017 ◽  
Vol 71 (1) ◽  
pp. 169-188 ◽  
Author(s):  
E. Shafiee ◽  
M. R. Mosavi ◽  
M. Moazedi
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Late Phase ◽  
Machine Learning Algorithms ◽  
Computational Method ◽  
Single Frequency ◽  
Detection Accuracy ◽  
Gps Receiver ◽  
Navigation Data ◽  
Spoofing Detection

The importance of the Global Positioning System (GPS) and related electronic systems continues to increase in a range of environmental, engineering and navigation applications. However, civilian GPS signals are vulnerable to Radio Frequency (RF) interference. Spoofing is an intentional intervention that aims to force a GPS receiver to acquire and track invalid navigation data. Analysis of spoofing and authentic signal patterns represents the differences as phase, energy and imaginary components of the signal. In this paper, early-late phase, delta, and signal level as the three main features are extracted from the correlation output of the tracking loop. Using these features, spoofing detection can be performed by exploiting conventional machine learning algorithms such as K-Nearest Neighbourhood (KNN) and naive Bayesian classifier. A Neural Network (NN) as a learning machine is a modern computational method for collecting the required knowledge and predicting the output values in complicated systems. This paper presents a new approach for GPS spoofing detection based on multi-layer NN whose inputs are indices of features. Simulation results on a software GPS receiver showed adequate detection accuracy was obtained from NN with a short detection time.

scholarly journals INS/GPS for High-Dynamic UAV-Based Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Junchuan Zhou ◽  
Stefan Knedlik ◽  
Otmar Loffeld
Keyword(s):  
Carrier Phase ◽  
Velocity Estimation ◽  
Estimation Accuracy ◽  
Processing Load ◽  
Estimation Errors ◽  
Integration Interval ◽  
Sequential Processing ◽  
Large Velocity ◽  
Different Types ◽  
High Dynamic

The carrier-phase-derived delta pseudorange measurements are often used for velocity determination. However, it is a type of integrated measurements with errors strongly related to pseudorange errors at the start and end of the integration interval. Conventional methods circumvent these errors with approximations, which may lead to large velocity estimation errors in high-dynamic applications. In this paper, we employ the extra states to “remember” the pseudorange errors at the start point of the integration interval. Sequential processing is employed for reducing the processing load. Simulations are performed based on a field-collected UAV trajectory. Numerical results show that the correct handling of errors involved in the delta pseudorange measurements is critical for high-dynamic applications. Besides, sequential processing can update different types of measurements without degrading the system estimation accuracy, if certain conditions are met.

scholarly journals Assessment of the position accuracy of a single-frequency GPS receiver designed for electromagnetic induction surveys

2018 ◽  
Vol 20 (1) ◽  
pp. 19-39 ◽  
Author(s):  
Sebastian Rudolph ◽  
Ben Paul Marchant ◽  
Lutz Weihermüller ◽  
Harry Vereecken
Keyword(s):  
Electromagnetic Induction ◽  
Single Frequency ◽  
Gps Receiver ◽  
Position Accuracy

Extracting Ionosphere Scintillations Index Based on Single Frequency GPS Software Receiver

2012 ◽  
Vol 190-191 ◽  
pp. 1136-1143
Author(s):  
Zhi Huang ◽  
Hong Yuan ◽  
Qi Yao Zuo
Keyword(s):  
High Speed ◽  
Single Frequency ◽  
Scintillation Index ◽  
Ionospheric Scintillation ◽  
Signal Acquisition ◽  
Gps Receiver ◽  
Signal Loss ◽  
Software Receiver ◽  
Ionospheric Plasma Density ◽  
Gps Signal Acquisition

Scintillations are caused by ionospheric plasma-density irregularities and can lead to signal power fading, loss of lock of the carrier tracking loop in the GPS receiver. The traditional method of monitoring and mitigating scintillation is to transform commercial GPS receiver with modified hardware and embedded software. To better facilitate advance development GPS receiver under different condition, GPS software scintillation receiver is designed in this paper. The hardware scheme of high-speed GPS signal acquisition system is first discussed and implemented with FPGA and DSP architecture. Then, we describe receiver software processing algorithm, particularly the portion involving the scintillation signal acquisition and tracking, ionospheric scintillation index extracting and scintillation monitoring. The performance of software receiver is demonstrated under scintillation conditions. Relevant results show that software-receiver based approach can avoid weak signal loss and extract effectively ionospheric scintillation parameter compared with the traditional extracting method. Software receiver is suitable and reliable for the ionospheric scintillations monitoring, and can provide theoretical foundations and experimental preparations for future scintillation studies implemented with Chinese indigenous BeiDou-Ⅱ navigation and poisoning system.

GPS RECEIVERS TIMING DATA PROCESSING USING NEURAL NETWORKS: OPTIMAL ESTIMATION AND ERRORS MODELING

2007 ◽  
Vol 17 (05) ◽  
pp. 383-393 ◽  
Author(s):  
M. R. MOSAVI
Keyword(s):  
Neural Networks ◽  
Outdoor Recreation ◽  
Optimal Estimation ◽  
Single Frequency ◽  
Gps Receiver ◽  
Commercial Aviation ◽  
Gps Receivers ◽  
Before And After ◽  
Timing Data

The Global Positioning System (GPS) is a network of satellites, whose original purpose was to provide accurate navigation, guidance, and time transfer to military users. The past decade has also seen rapid concurrent growth in civilian GPS applications, including farming, mining, surveying, marine, and outdoor recreation. One of the most significant of these civilian applications is commercial aviation. A stand-alone civilian user enjoys an accuracy of 100 meters and 300 nanoseconds, 25 meters and 200 nanoseconds, before and after Selective Availability (SA) was turned off. In some applications, high accuracy is required. In this paper, five Neural Networks (NNs) are proposed for acceptable noise reduction of GPS receivers timing data. The paper uses from an actual data collection for evaluating the performance of the methods. An experimental test setup is designed and implemented for this purpose. The obtained experimental results from a Coarse Acquisition (C/A)-code single-frequency GPS receiver strongly support the potential of methods to give high accurate timing. Quality of the obtained results is very good, so that GPS timing RMS error reduce to less than 120 and 40 nanoseconds, with and without SA.

Sign in / Sign up

Export Citation Format

Share Document