Showing 14 results for Gps
M. H. Refan, H. Valizadeh,
Volume 8, Issue 3 (9-2012)
Abstract
Accurate and reliable time is necessary for financial and legal transactions, transportation, distribution systems, and many other applications. Time synchronization protocols such as NTP (the Network Time Protocol) have kept clocks of such applications synchronized to each other for many years. Nowadays there are many commercial GPS based NTP time server products at the market but they almost have a high price. In this paper we are going to use a low cost GPS engine to build a time server to provide time synchronization with accuracy of a few milliseconds. This time server is relatively very cheap and it can be used in almost all typical applications. We also proposed a software based NTP time server implemented in MATLAB as well.
M H Refan, A Dameshghi, M Kamarzarrin,
Volume 9, Issue 4 (12-2013)
Abstract
Differential base station sometimes is not capable of sending correction information for minutes, due to radio interference or loss of signals. To overcome the degradation caused by the loss of Differential Global Positioning System (DGPS) Pseudo-Range Correction (PRC), predictions of PRC is possible. In this paper, the Support Vector Machine (SVM) and Genetic Algorithms (GAs) will be incorporated for predicting DGPS PRC information. The Genetic Algorithm is employed to feature subset selection. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy in Real Time DGPS. Given a set of data received from low cost GPS module, the GASVM can predict the PRC precisely when the PRC signal is lost for a short period of time. This method which is introduced for the first time for prediction of PRC is compared to other recently published methods. The experiments show that the total RMS prediction error of GASVM is less than 0.06m for on step and 0.16m for 10 second ahead cases
M. R. Mosavi, S. Azarshahi, I. Emamgholipour , A. A. Abedi,
Volume 10, Issue 1 (3-2014)
Abstract
In present study, using Least Squares (LS) method, we determine the position smoothing in GPS single-frequency receiver by means of pseudo-range and carrier phase measurements. The application of pseudo-range or carrier phase measurements in GPS receiver positioning separately can lead to defects. By means of pseudo-range data, we have position with less precision and more distortion. By use of carrier phase data, we do not have absolute position and just dislocation is available, but the accuracy is high. In present research, we have combined pseudo-range and carrier phase data using LS method in order to determine GPS receiver's position smoothing. The results of comparison by LS method show less RMS error, less calculation volume and more smoother in using carrier phase-pseudo-range data together relative to pseudo-range data in isolation.
M. R. Mosavi, Z. Shokhmzan,
Volume 11, Issue 3 (9-2015)
Abstract
The Global Positioning System (GPS) signals are very weak signal over wireless channels, so they are vulnerable to in-band interferences. Therefore, even a low-power interference can easily spoof GPS receivers. Among the variety of GPS signal interference, spoofing is considered as the most dangerous intentional interference. The spoofing effects can mitigate with an appropriate strategy in the receiver. In this paper, we use methods of adaptive filter based on Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) algorithms in-order to defense against spoofing. The proposed techniques are applied in the acquisition stage of the receiver. The proposed methods have been implemented on real dataset. The results explain that the suggested algorithms significantly decrease spoofing. Also, they improve Position Dilution of Precision (PDOP) parameter. Based on the results, NLMS algorithm has better performance than LMS algorithm.
M. Mousavi Moaiied, M. R. Mosavi,
Volume 12, Issue 1 (3-2016)
Abstract
In this paper, combined GPS and GLONASS positioning systems are discussed and some solutions have been proposed to improve the accuracy of navigation. Global Satellite Navigation System (GNSS) is able to provide position, velocity and time with respect to coordinated universal time. GNSS positioning is based on received satellite signals, so its performance is highly dependent on the quality of these received signals. The effect of noise and multi-path can often be large enough to produce significant errors in positioning. Satellite navigation is difficult in this situation. In such circumstances, GPS or GLONASS alone are often not able to ensure consistency and accuracy in positioning due to the absence (or low quality) of signals. The combination of these two systems is an appropriate solution to improve the situation. In positioning a receiver, one of the ways that is often used to reduce the error due to observation noise and calculation errors is Kalman Filter (KF) estimation. In this paper, some changes in the structure of the KF is applied to improve the accuracy of positioning. Process of updating KF's gain, is done in fuzzy form based on the parameters available in RINEX files, including the P code pseudo-range used as an input of the proposed fuzzy system. Simulation results show that applying a fuzzy KF based on P code pseudo-range on the available data sets, in terms of noise and blocking condition, reduces the positioning error respectively from 24 to 14 meters and 90 to 25 meters.
A. A. Abedi, M. R. Mosavi, K. Mohammadi, M. R. Daliri,
Volume 12, Issue 3 (9-2016)
Abstract
One of the instruments for determination of position used in several applications is the Global Positioning System (GPS). With a cheap GPS receiver, we can easily find the approximate position of an object. Accuracy estimation depends on some parameters such as dilution of precision, atmospheric error, receiver noise, and multipath. In this study, position accuracy with GPS receiver is classified in three classes. Nine classification methods are utilized and compared. Finally, a new method is selected for classification. Results are verified with experimental data. Success rate for classificationis approximately 84%.
M. Moazedi, M. R. Mosavi, A. Sadr,
Volume 13, Issue 2 (6-2017)
Abstract
Global Positioning System (GPS) spoofing could pose a major threat for GPS navigation systems, so the GPS users have to gain a better understanding of the broader implications of GPS. In this paper, a plenary anti-spoofing approach based on correlation is proposed to distinguish spoofing effects. The suggested method can be easily implemented in tracking loop of GPS receiver. We will study a real-time spoof recognition with a clear certainty by introducing a reliable novel metric. As a primary step, the proposed technique is implemented in software receiver to prove the concept of idea in a multipath-free scenario. Three rooftop data sets, collected in our GPS laboratory, are used in the performance assessment of the proposed method. The results indicate that investigated algorithm is able to perform a real-time detection in all date sets.
M. R. Mosavi, A. Rashidinia,
Volume 13, Issue 3 (9-2017)
Abstract
Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Function (RBF) has been developed. In many previous works all parameter of RBF NN are optimizing by evolutionary algorithm such as Particle Swarm Optimization (PSO), but in our approach shape parameter and centers of RBF NN are calculated in better way, in addition, search space for PSO algorithm will be reduced which cause more accurate and faster approach. The obtained results show that RMS has been reduced about 0.13 meter. Moreover, results are tabulated in the tables which verify the accuracy and faster convergence nature of our approach in both on-line and off-line training methods.
Z. Shokhmzan, M. R. Mosavi, M. Moazedi,
Volume 13, Issue 4 (12-2017)
Abstract
The vulnerability of civil GPS receiver to interference may be intentional or unintentional. Among all types of interference, replay attack intended as the most dangerous intentional one. The signal structure of replay attack is almost the same with the satellite signal. The interference effects can be reduce with the design of an appropriate filter in the receiver. This paper presents two methods based on Finite Impulse Response (FIR) filter in frequency and time domain to mitigate the interference effect on GPS signals. Designed FIR filter protects GPS against the replay attack. The suggested filter is applied in the acquisition of the receiver. The proposed method has been implemented on collected dataset. The results show that the proposed algorithms significantly reduce interference. Also, they improve Position Dilution of Precision (PDOP) parameter. Based on the results, the FIR filter technique in time domain has better performance than the frequency domain.
H. Sedighy,
Volume 14, Issue 2 (6-2018)
Abstract
A null steering GPS antenna array is designed in this paper. In the proposed method, the exact full wave antenna radiation properties with the effect of mutual couplings and nearby scatterers are considered to calculate the array steering vector, precisely. Although the proposed method is not constrained by the array geometry and the antenna element specifications, a five patch antenna elements with planar array geometry is designed and simulated as an anti jam GPS antenna example. The simulation results show the importance of the mutual coupling effects. Moreover, the results verify the proposed method ability to encounter with the multiple GPS jammer sources. Finally, the effect of jammer power is investigated which shown that the antenna performance is increased by jammer power enhancement.
P. Teymouri, M. R. Mosavi, M. Moazedi,
Volume 14, Issue 3 (9-2018)
Abstract
Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive filters to eliminate interference, obtain an estimate of interfering signal and subtract that from the corrupted signal. So, what remains in the output is the desired signal. Here, for updating the filter coefficients adaptive algorithms in both time (statistical and deterministic) and transform domain will be studied. The proposed adaptive filter is applied to a batch of spoofing GPS data in pseudo-range level. The results indicate that all investigated algorithms are able to reduce positioning steady-state miss-adjustment up to 70 percent. In this context, the variable step-size least mean square algorithm performs better than others do.
S. Juneja, R. Sharma,
Volume 15, Issue 4 (12-2019)
Abstract
Design of Global Positioning System (GPS) receiver with a low noise amplifier (LNA) in the front end remains a major design requirement for the success of modern day navigation and communication system. Any LNA is expected to meet the requirements like its ability to add the least amount of noise while providing sufficient gain, perfect input and output matching, and high linearity. However, most of the reported designs of LNAs present the need for striking a trade-off between these design parameters in order to obtain the desired performance for a particular RF receiver. This paper presents high gain (21dB), high input matched (-29dB), high reverse isolation (-41dB) and low noise figure (< 2dB) narrowband LNA for extremely low power level GPS L1 band signals broadcasting at 1.57GHz with a channel bandwidth of 10MHz. Inductive source degeneration topology is employed for the design and all the matching inductors in the circuit are used with fixed quality factor (Q) to model the losses for better tuning and matching. The design is carried out on Cadence Virtuoso Tool version IC6.1.6 and Spectre version MMSIM13.1 at 0.18µm technology node using a generic process development kit. Detailed mathematical analysis of the design is done and all the DC parameters like values of transconductance, gate source capacitance, drain source voltage, drain current, etc. are reported. Graphical analysis using Smith chart is carried out to present the results and to bring forth the trade-offs involved in the design. LNA draws 5mA current from 1.2V supply voltage and offers good linearity that is sufficient for GPS application and is measured by input intercept point 3 (IIP3 < ‑4dBm).
M. H. Refan, A. Dameshghi,
Volume 16, Issue 2 (6-2020)
Abstract
Geometric Dilution of Precision (GDOP) is a coefficient for constellations of Global Positioning System (GPS) satellites. These satellites are organized geometrically. Traditionally, GPS GDOP computation is based on the inversion matrix with complicated measurement equations. A new strategy for calculation of GPS GDOP is construction of time series problem; it employs machine learning and artificial intelligence methods for problem-solving. In this paper, the Time Delay Neural Network (TDNN) is introduced to the GPS satellite DOP classification. The TDNN has a memory for archiving past event that is critical in GDOP approximation. The TDNN approach is evaluated all subsets of satellites with the less computational burden. Therefore, the use of the inverse matrix method is not required. The proposed approach is conducted for approximation or classification of the GDOP. The experiments show that the approximate total RMS error of TDNN is less than 0.00022 and total performance of satellite classification is 99.48%.
K. Zarrinnegar, S. Tohidi, M. R. Mosavi, A. Sadr, D. M. de Andrés,
Volume 19, Issue 1 (3-2023)
Abstract
The Global Positioning System (GPS) is vulnerable to various deliberate and unintentional interferences. Therefore, identifying and coping with various interferences in this system is essential. This paper analyzes a method of reducing the dimensions of Cross Ambiguity Function (CAF) images in improving the identification of spoofing interference at the GPS using Multi-Layer Perceptron Neural Network (MLP NN) and Convolutional Neural Network (CNN). Using the proposed method reduces data complexity, which can reduce the number of learning data requirements. The simulation results indicate that, by applying the proposed image processing algorithm for different dimensions of CAF images, the CNN performs better than MLP NN in terms of training accuracy; the MLP NN is superior to CNN in terms of convergence speed of training. In addition, the results demonstrate that the operation of the proposed method is appropriate in the case of small-delay spoofed signals. Therefore, for the intervals above 0.25 code chip, the proposed method detects spoofing attacks with a correct detection probability close to one.