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Item Open Access Aplicación del Algoritmo de Redes Elásticas en imágenes satelitales(Universidad Nacional Mayor de San Marcos, Vicerrectorado de Investigación y Posgrado, 2018) Príncipe Aguirre, Romel Erick; Willems, BramEsta investigación se realizó en el Santuario Nacional Los Manglares de Tumbes (SNLMT), ubicado en el distrito de Zarumilla departamento de Tumbes, está orientada a implementar una metodología que permita caracterizar la cobertura de manglar. Para ello, se analizó y procesó la imagen del sensor TM del satélites LandSat 5 evaluando una serie de parámetros relacionados a la superficie del suelo, tales como SAVI (Índice de vegetación ajustado al suelo), NDVI (Índice de vegetación de diferencia normalizada) y NDWI (Índice de agua de diferencia normalizada) con miras a establecer el índice óptimo que permita discriminar las diferentes componentes de cobertura de suelo del Santuario. El indice óptimo (SAVI) antes descrito fue introducido en el Algoritmo de las Redes Elásticas (ENA, por sus siglas en ingles) para la clasificación de la cobertura de suelo del SNLMT. Las imágenes construidas a partir de los resultados ENA, fueron sometidos al proceso de validación empleando métodos convencionales como el algoritmo de máxima verosimilitud (AMV). Tal proceso de validación consistió en realizar los análisis y comparaciones de las gráficas de firmas espectrales promedio de cada clase informacional obtenidos tanto con ENA y AMV, dando como resultados similares gráficas donde el RMSE fue por debajo de 0.052 (adimensional) y el factor de correlación sobre r=0.886. Esto indica que el método ENA resulta ser una herramienta eficaz para la subdivisión de clases de cobertura manglar.Item Restricted Spectral Analysis of Incoherent Scatter Radar Signals in Faraday/Double Pulse Experiments at the Jicamarca Radio Observatory(IEEE, Institute of Electrical and Electronics Engineers, 2021) Flores, Roberto; Milla, Marco; Kuyeng, KarimThe Jicamarca incoherent scatter radar can be operated in different modes to measure the main physical parameters of the equatorial ionosphere. One of these modes is the Faraday/Double Pulse experiment that was designed to estimate F -region plasma densities and electron/ion temperatures by pointing the Jicamarca antenna beam off-perpendicular to the geomagnetic field. For several years, the data processing for this mode was performed in time domain (correlation analysis), but sometimes the data is contaminated with frequency interference and other unwanted signals that are not easy to remove. To obtain better results, a spectral analysis procedure for this mode has been implemented in Signal Chain, a python-based radar signal processing library developed at the Jicamarca Radio Observatory. Signal Chain includes algorithms for interference and clutter removal to clean the spectral data before estimating the geophysical parameters. The procedure applies an outlier removal algorithm before calculating incoherently averaged power spectra. This algorithm, based on the Hildebrand-Sekhon method, is applied to sequences of spectral data for each frequency bin. Then, the DC clutter from the self- and cross-spectra is removed as a second step in the cleaning process. In this work, we present the results obtained with the spectral analysis procedure applied to the the FaradaylDouble Pulse experiment and compared the electron densities estimated with this method with the ones obtained with the standard correlation analysis.Item Restricted SOPHy: Scanning-system for Observations of Peruvian Hydrometeorological-events(IEEE, Institute of Electrical and Electronics Engineers, 2021) Espinoza, Juan C.; Scipión, Danny; Valdez, Alexander; Verástegui, JoaquínIn this paper we present the current progress in the construction of the first X-band dual-pol mobile weather radar (SOPHy) in Peru. This portable mobile system allows scans in azimuth and elevation with a maximum range of 60 km. The radar transmission and reception systems are based on SDR (Software Defined Radio) technologies for configuration flexibility. The objective of the radar is to study precipitation in an area of several tens of kilometers around the radar, in order to research the climate and atmospheric conditions in Peru.Item Restricted Design and development of a low-cost wireless network using IoT technologies for a mudslides monitoring system(IEEE, Institute of Electrical and Electronics Engineers, 2021) Meléndez Coveñas, Frank Enrique; Palomares, Ricardo; Milla, Marco; Verastegui, Joaquin; Cornejo, JoséThe city of Lima - Peru is affected periodically by mudslides and floods caused by torrential rains near Lima's mountain region. The Jicamarca ravine is especially affected by this phenomenon and is also critical to the population because of its proximity to SEDAPAL's water treatment plant that provides drinking water service to approximately 80% of homes in Lima city. In addition to this, there are a lot of houses located near the riversides affected by the mudslides that could be affected by the overflows. This paper describes the implementation of a low-cost wireless sensor network based on Internet of Things (IoT) technologies designed for monitoring mudslides events made by the association of the Professional School of Electronic Engineering and Telecommunications of the Universidad Nacional Tecnológica de Lima Sur and the Radio Observatorio de Jicamarca, research facility of the Instituto Geofísico del Perú. The network consists of various monitoring stations based on the ESP32 microcontroller and it takes advantage of the Long-Range mode of this device. The radio links created have a range of more than 1 km and all of them are connected to one access point which has a connection to the internet using the IoT technology of the cellular mobile network. The access point sends data to a server in the cloud allowing access to sensors remotely without putting people's lives at risk. This project is part of a program of the Instituto Geofísico del Perú with the goal of implementing a National Mudslide Monitoring Center.Item Restricted Design of a Programmable Radar Controller ASIC on VHDL for a Modular Radar System(IEEE, Institute of Electrical and Electronics Engineers, 2021) Verastegui, Joaquin; Manay, Ivan; Pacheco, Edgardo E.; Milla, MarcoThe Jicamarca Radio Observatory (JRO), funded by the USA National Science Foundation (NSF), operates several radars for different applications, from the main radar, an incoherent scatter radar used mainly for ionospheric activity observations, to ionosondes and wind profilers. Most of these radars use a centralized modular control system that commands all the radar sequences that require the radar modules, these tasks and sequences are controlled by pulsed digital signals. The device responsible for this operation is called the Radar Controller. A large number of customized Radar Controller versions were developed and built at JRO for decades, since the utilization of its first acquisition system. The current version of the Radar Controller is based on an RTL design written on VHDL language that implements a custom arbitrary waveform generator connected to an SRAM memory that stores all the data a given waveform needs. The Radar Controller uses a register based architecture to communicate between blocks internally. In JRO we use a Spartan 6 FPGA and it is controlled by a Tiva C microcontroller board which has an Ethernet port. A Restful API has been implemented on the microcontroller for user configuration. This paper will cover the VHDL RTL design of the current version of the Radar Controller core.Item Restricted Mapping irregularities in the postsunset equatorial ionosphere with an expanded network of HF beacons(American Geophysical Union, 2021-07) Hysell, D. L.; Rojas, E.; Goldberg, H.; Milla, Marco; Kuyeng, K.; Valdez, A.; Morton, Y. T.; Bourne, H.Data from a network of high-frequency (HF) beacons deployed in Peru are used to estimate the regional ionospheric electron density in a volume. Pseudorange, accumulated carrier phase, and signal power measurements for each of the 36 ray paths provided by the network at a 1 min cadence are incorporated in the estimates. Additional data from the Jicamarca incoherent scatter radar, the Jicamarca sounder, and GPS receivers can also be incorporated. The electron density model is estimated as the solution to a global optimization problem that uses ray tracing in the forward model. The electron density is parametrized in terms of B-splines in the horizontal direction and generalized Chapman functions or related functions in the vertical. Variational sensitivity analysis has been added to the method to allow for the utilization of the signal power observable which gives additional information about the morphology of the bottomside F region as well as absorption including absorption in the D and E regions. The goal of the effort is to provide contextual information for improving numerical forecasts of plasma interchange instabilities in the postsunset F region ionosphere associated with equatorial spread F (ESF). Data from two ESF campaigns are presented. In one experiment, the HF data revealed the presence of a large-scale bottomside deformation that seems to have led to instability under otherwise inauspicious conditions. In another experiment, gradual variations in HF signal power were found to be related to the varying shape of the bottomside F layer.Item Restricted Ionospheric echo detection in digital ionograms using convolutional neural networks(American Geophysical Union, 2021-08) De la Jara, César; Olivares, C.An ionogram is a graph of the time that a vertically transmitted wave takes to return to the earth as a function of frequency. Time is typically represented as virtual height, which is the time divided by the speed of light. The ionogram is shaped by making a trace of this height against the frequency of the transmitted wave. Along with the echoes of the ionosphere, ionograms usually contain a large amount of noise and interference of different nature that must be removed in order to extract useful information. In the present work, we propose a method based on convolutional neural networks to extract ionospheric echoes from digital ionograms. Extraction using the CNN model is compared with extraction using machine learning techniques. From the extracted traces, ionospheric parameters can be determined and electron density profile can be derived.