Eniuce Menezes de Souza

An Effective Wavelet Method to Detect and Mitigate Low-Frequency Multipath Effects

To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The “ground truth” coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

GPS Satellite Kinematic Relative Positioning: Analyzing and Improving the Functional Mathematical Model Using Wavelets

Although GPS kinematic relative positioning can provide high accuracy, GPS observables, like any other kind of measurement, are not free of errors. Indeed, they have several kinds of errors. In this paper, we show how to construct a functional mathematical model within the context of a Kalman Filter in order to eliminate most of these errors. Furthermore, we discuss how the multipath effect, a kind of error not modeled in the functional model, can be corrected using the proposed wavelet method. The behavior of the double difference functional model in the kinematic mode is also demonstrated and analyzed aiming to provide better insight into the problem. The results obtained from the multipath experiments were very promising and are presented here.

S 4 index: Does it only measure ionospheric scintillation?

The study of ionospheric scintillation has played a critical role in ionospheric research and also in satellite positioning. This is due to the growing influence of GNSS in navigation and remote sensing activities and also because the scintillation severely degrades the performance of this system. The main parameter that has been used to investigate the ionospheric scintillation impact on quality of GNSS satellite signals is the S4 index. However, we show that other effects such as multipath may mask the scintillation effects. Furthermore, we propose a method to separate the effect of multipath from scintillation in the S4 index by a non-decimated wavelet multiscale decomposition, which is shift invariant and more appropriate to use in the analysis of time series. The results show that the multipath effect is evident in the smoother scales of multiscale decomposition by wavelet in the weak scintillation period. Once identified and estimated, this effect can be removed from the S4 index series during strong scintillation periods and it becomes not significant in the scintillation S4 index wavelet analysis. Investigations using data from different stations and satellites demonstrate that the effect of ionospheric scintillation varies with station location and elevation angle of the satellite. Therefore, each case must be treated individually.

Avaliação do desempenho da solução das ambiguidades no posicionamento baseado em redes sob influência da atividade ionosférica

A solucao das ambiguidades e o processo de determinar o numero desconhecido de ciclos inteiros de dupla diferenca (DDs) da fase da onda portadora, sendo um pre-requisito para a obtencao de alta acuracia no posicionamento baseado em redes. Para realizar este posicionamento com o uso de VRS (Estacao de Referencia Virtual), deve haver uma comunicacao entre o usuario e a estacao de base, para que ele possa enviar a sua localizacao e possa receber dados da VRS. Os dados da VRS sao gerados a partir das correcoes obtidas para uma estacao de base localizada perto do usuario. Estas correcoes sao compostas por erros atmosfericos (ionosfera e troposfera), os quais podem ser estimados utilizando os dados das estacoes de referencia da rede. O desafio e solucionar rapidamente as ambiguidades como inteiros. Neste trabalho, sao investigadas algumas estrategias de processamento para a obtencao da solucao das ambiguidades no posicionamento baseado em redes com dados GPS de dupla frequencia. Esta estrategia sugere utilizar o modelo ionosfera ponderada, incorporando as coordenadas das estacoes de referencia da rede e uma informacao a priori sobre os atrasos ionosfericos, utilizando os metodos LAMBDA e o Fixed Failure Ratio Test.

Modelagem e investigação de periodicidades nas taxas de internações por diarreia antes e após a vacina contra o rotavírus no estado do Paraná

No estudo de series temporais no dominio de frequencias, a analise de Fourier ou analise harmonica e bastante utilizada para encontrar periodicidades desconhecidas. Tal procedimento decompoe a serie em componentes periodicos, ou seja, a analise de Fourier corresponde a particao da variabilidade da serie em componentes de frequencias. Logo, como por ser visto em [2], considerando o modelo da serie temporal dado por uma combinacao linear de harmonicos (componentes senoidais) da seguinte forma [...]