Design of complete software GPS signal simulator with low complexity and precise multipath channel model

Elango, G. Arul; Sudha, Gnanou Florence

doi:10.1016/j.jesit.2016.03.002

Cited by 11 publications

(12 citation statements)

References 12 publications

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“…The experiment shows that the simulation results and waveform display are in accordance with the theoretical values. In the experiment, the research of signal interference (such as multipath interference [6]) and related algorithms (kalman filtering) needs to be further studied. …”

Section: Resultsmentioning

confidence: 99%

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Research and Simulation of GPS Navigation Signals

Cao¹,

Wang²

2017

dtcse

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There are most important strategic significance in our country as well as the carrier rocket, ballistic missiles, the development of the manned space engineering that GPS signal simulation of satellite navigation system has. The structure and principle of GPS navigation and positioning signal were discussed in detail in this paper, with practicality as the starting point, the navigation message is transmitted by the use of pseudo random noise code phase-modulated signal, and the method of direct sequence spread spectrum modulation system is used to simulate the signal of GPS satellite orbit based on the MATLAB/Simulink platform. Then the simulation research and analysis of C/A code and P code in the frequency domain and time domain with it`s correlation is carried on, at the same time, the C/A code frequency domain is captured by using the fast Fourier transform method (FFT).finally the space transmission characteristics of GPS signal is simulated under Gaussian noise.it is show that the simulation result is close to the theoretical value, and the accuracy is better.

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Section: Resultsmentioning

confidence: 99%

“…FFT is a kind of DFT efficient algorithm, called Fast Fourier transform [6], which is gained by improve the discrete Fourier transform algorithm according to the odd, even, virtual and real characteristics of discrete Fourier transform.…”

Section: Fft Frequency Domain Capturementioning

confidence: 99%

Research and Simulation of GPS Navigation Signals

Cao¹,

Wang²

2017

dtcse

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“…However, in fixed wireless communication systems, both the transmitter and the receiver are stationary and time-variations are actually due to moving scatterers. Filtering White Gaussian Noise (FWGN), AR Model and Sum of Sinusoidal (SOS) exhibits the property of the Rayleigh model [4]. The typical FWGN and AR Model are shown in Figure 3(b) and (c).…”

Section: Overview Of Multipath Channel Modelmentioning

confidence: 99%

Review on Sparse-Based Multipath Estimation and Mitigation: Intense Solution to Counteract the Effects in Software GPS Receivers

Elango¹,

Kumar²,

Kumar³

et al. 2018

Multifunctional Operation and Application of GPS

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Multipath is the major concern in GPS receivers that fade the actual GPS signal causes positioning error up to 10 m so special care need to be taken to mitigate the multipath effects. Numerous methods like hardware based antenna arrays technique, receiver based narrow correlator receiver, double -delta discriminator, Adaptive Multipath Estimator, Wavelet Transformation and Particle filter, Kalman filter based post receiver methods etc. used to resolve the problem. But some of the methods can only reduce code multipath error but not effective in eliminating carrier multipath error. Most of these techniques are based on the assumption that the Line-of-Sight (LOS) signal is stronger than the Non-Line of-Sight (NLOS) signals. However, in the scenarios where the LOS signal is weaker than the composite multipath signal, this approach may result in a bias in code tracking. In this chapter, different types of multipath mitigation and its limitation are described. The recent development in sparse signal processing based blind channel estimation is investigated to compensate the multipath error. The Rayleigh and Rician fading model with different multipath parameters are simulated to test the urban scenario. The inverse problem of finding the GPS signal is addressed based on the deconvolution approach. To solve linear inverse problems, the suitable kind of appropriate objective function has been formulated to find the signal of interest. By exploiting this methods, the signal is observed and the carrier and code tracking loop parameters are computed with minimal error.

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“…Simulations can be done on various levels starting from the molecular level and the study of electric fields, to the level of individual receiver components [6,7], to the level of pseudoranges [8], and on to the level of navigation solutions where the receiver point position can be represented by a Gaussian distribution [9]. Each of these levels offers a different representation of the reality.…”

Section: Introductionmentioning

confidence: 99%

Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance

Lehtola

Söderholm

Koivisto

et al. 2019

Sensors

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GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.

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Design of complete software GPS signal simulator with low complexity and precise multipath channel model

Cited by 11 publications

References 12 publications

Research and Simulation of GPS Navigation Signals

Research and Simulation of GPS Navigation Signals

Review on Sparse-Based Multipath Estimation and Mitigation: Intense Solution to Counteract the Effects in Software GPS Receivers

Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance

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