The HF radar is a network of HF radio beacons and receivers for ionospheric sounding, and it has been operating in Peru since 2016. The purpose of this instrument is to measure the group delay, Doppler shift, power, and other parameters in order to estimate the regional plasma density as a function of space and time. This information is crucial for forecasting the occurrence of Spread-F. To improve the quality of the spectral data, two changes were made. The first one involved transmitting frequencies separated by 3.3 Hz in each transmission station, which allowed to spectrally separate and identify the signals coming from a given station, displacing the cross-talk in frequency but not eliminating it. Therefore, the second change was made, which corresponds to the development of an algorithm that extracts only the signals of interest from the measured spectrum. It is capable of detecting clusters of data in the spectra classifying them as coherent echoes, while noise sectors are discarded. The algorithm procedure and the comparisons of the spectra and final data are shown in this work.

The 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.

The 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.

In 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.

The 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.