Artemis Homepage
Artemis is a software designed to assist radio frequency (RF) signal identification and storage. It simplifies real-time spectrum analysis by leveraging one of the most extensive and community-driven databases, containing over 520 recognized signals. This comprehensive software solution allows users to collect RF signals with specific parameters such as frequency, bandwidth, modulation, etc. Users can also store spectrum waterfalls, audio samples, and all types of documents for future reference. Artemis provides a robust platform to manage a wide range of RF data with precision and ease.
"},{"location":"acf_analysis/","title":"Autocorrelation Function (ACF)","text":""},{"location":"acf_analysis/#theoretical-introduction","title":"Theoretical Introduction","text":"Correlation functions are valuable mathematical tools utilized across various scientific disciplines, including engineering, physics, and chemistry. The cross-correlation function, commonly defined as a sliding inner (dot) product, quantifies the similarity between two signals as a function of a temporal shift applied to one of them:
\\[ \\left[ k*l \\right]\\equiv \\int_{-\\infty}^{+\\infty}k^{*}(t)l(t+\\tau)dt \\]where \\(k\\) and \\(l\\) are two general non-discrete functions without discontinuity, \\(k^{*}\\) is the complex conjugate of \\(k\\) and \\(\\tau\\) is the lag (time delay for signal analysis). This representation is closely related to the convolution theorem by the following relationship:
\\[ k(t)*l(t)\\equiv k^{*}(-t)*l(t) \\]In our case, the signal must be compared with itself to identify periodic patterns or detect anomalous high degrees of similarity within a given time interval. To achieve this objective, we can employ the Autocorrelation Function (ACF), which is essentially the cross-correlation of a signal with itself, where \\(k(t)=l(t)\\). The following equation defines the ACF, derived from a straightforward modification of the initial equation:
\\[ \\left[ k*k \\right](\\tau)\\equiv \\int_{-\\infty}^{+\\infty}k^{*}(t)k(t+\\tau)dt \\]Within a discrete data set composed by \\(Y(t)\\) records we can easily calculate autocorrelation from:
\\[ \\rho_{\\tau}=\\frac{\\sum_{i=1}^{N-\\tau}(Y_i-\\bar{Y})(Y_{i+\\tau}-\\bar{Y})}{\\sum_{i=1}^{N}(Y_i-\\bar{Y})^2} \\]where \\(Y_{i+\u03c4}\\) is a lagged data by \\(\u03c4\\) of \\(Y_i\\) and \\(\\bar{Y}\\) is the average value of the original data set. Entire denominator is used to keep the normalization condition, indeed \u03c1\u03c4 can assume a value between -1 (exact anticorrelation) and +1 (exact correlation). A complete correlation can be only achieved with a perfect overlap of the analyzed function with it self; the simple way to verify that is when \\(\u03c4=0\\)
"},{"location":"acf_analysis/#example-acf-analysis","title":"Example: ACF Analysis","text":""},{"location":"acf_analysis/#stanag-4285","title":"STANAG 4285","text":"The first example will be a NATO standard known as STANAG 4285. You can download a .wav sample from HERE.
Your browser does not support the audio player.We start to collect some information about the structure of this signal: a good starting point is the official declassified NATO document dated 1989. The main frame structure can be found at Annex A-3/5 with a graphical view at Annex A-7, also reported below:
Summary
Therefore, a full sequence will be composed as the sum of all symbols reported above: 256 symbols recursively transmitted at the ratio of 2400 bauds means a redundancy of 106.66 ms. To analyze an unknown signal I strongly recommend Signal Analyzer (SA). SA is actually one of the most valuable and priceless software available by Sergey Makarov (\u041c\u0430\u043a\u0430\u0440\u043e\u0432 \u0421\u0435\u0440\u0433\u0435\u0439 \u041c\u0438\u0445\u0430\u0439\u043b\u043e\u0432\u0438\u0447, sadly passed away on 29 May 2012) and it used to perform several tests on data sample coded as .wav or .mp3 file. The signal waterfall is reported below:
When an Autocorrelation function is applied on selected data frame (see above), the result shows a clear recursive pattern with a gap of 106.244 ms between every peak as expected. An ACF refinement can be done into WaveForm windows where we can also notice an identical structure as reported by the specifications
Summary
New Database
Create a new database.
Load Database
Open the Database Manager windows in order to open, rename, or delete a database.
Import Database
Import an Artemis database with a standard .tar format.
Offline Importing of SigID Database
Sometimes it may happen that a computer does not have network access and unfortunately Artemis cannot download the SigID database. To solve this you can:
Export Database
Export the loaded database with a standard .tar format.
Edit Tags
Open the tags editor window. From here, you can add, rename, or delete tags. The tags can be added to a signal from the tags menu
Open Database Folder
Shows the folder of the currently loaded database in the explorer.
Preferences
Open the program settings window.
Exit
This will close the application.
New
Add a new signal to the database.
Edit
Edit the current/selected signal from the loaded database.
Check Report
Open the main Space Weather window and retrieve all the live data from Poseidon Crawler.
This is the signal list where all the database entries are shown. When a signal is selected, it will load on the right panel.
"},{"location":"basic_operations/#filter-by-namedescription","title":"Filter by Name/Description","text":"On top of the list, there is a field for filtering signals by name or any keyword inside the description of the signal: this filter has the highest priority among all the filters.
"},{"location":"basic_operations/#3-signal-menu","title":"3. Signal Menu","text":"Here you can swithc between the main signal window and the filter page.
"},{"location":"basic_operations/#4-tags","title":"4. Tags","text":"Associate Tag
Custom tags can be associated to the selected signal with the icon
Remove Tag
In order to remove a tag, just click on its badge.
Add/Rename Tag
To add a new tag open the Tags Editor in the main menu.
Click on the labels to add the corresponding parameter to the signal (e.g. click on Frequency to add a new frequency).
"},{"location":"basic_operations/#6-edit-parameter","title":"6. Edit Parameter","text":"Click on the parameter badge to open the Signal Editor windows. From here, you can edit or delete the corresponding parameter.
Parameter Description
All the parameters have a description field: if some text is added, it will appear when the corresponding parameter badge is hovered with the mouse pointer.
"},{"location":"basic_operations/#7-description","title":"7. Description","text":"This is the description of the signal and can be edited from the Main Menu (Signal/Edit...)
Markdown Supported
The Description field can render Markdown, a simple markup language for creating rich text using plain text. Headers, emphasis, lists, links, code blocks, and many more features for advanced text formatting. Markdown Basic Syntax
"},{"location":"basic_operations/#8-audio-sample","title":"8. Audio Sample","text":"This is a player where an audio sample of the signal can be played. To associate an audio file to be shown as the main audio sample, check in the extra menu below the signal spectrum.
"},{"location":"basic_operations/#9-image-sample","title":"9. Image Sample","text":"This is an image box that commonly contains the signal spectrum/waterfall. To associate an image file to be shown as the main image sample, check in the extra menu below the signal spectrum.
"},{"location":"basic_operations/#10-extra","title":"10. Extra","text":"This button is only available for the standard SigID wiki database and connects the local signal to its counterpart on the sigidwiki website.
This will open the Documents Manager. From here you can add any file (audio, image, pdf, etc.) to the signal entry. It is also possible to mark only one image and one audio to be shown on the main signal window.
"},{"location":"build_package/","title":"Build Package","text":"Building a distributable package with an executable for Artemis creates a practical solution for end-users, as they can run the application without needing to interact with the terminal and they can easily share the application as a standalone package.
"},{"location":"build_package/#requirements","title":"Requirements","text":"Info
We assume that Python is already installed on the system and the Artemis source code has been downloaded and extracted. If these prerequisites are not met, please follow steps 1 to 3 in the run from source section.
Cross-Compilation
An operating system that matches the target OS must be used to generate standalone packages, as Nuitka does not support cross-compilation. For example, you cannot build binaries on Windows that work on Linux or macOS.
"},{"location":"build_package/#simple-windows-windows","title":":simple-windows: Windows","text":""},{"location":"build_package/#procedure","title":"Procedure","text":"Open a PowerShell terminal in the main Artemis folder and execute the following command to start the build process:
.\\building\\Windows\\build_windows.ps1\nWait for the build process to complete. This may take a few minutes depending on your system's performance. Once the process finishes, check the artemis.dist/ directory: it will contain the standalone software with the artemis.exe executable.
Open a terminal in the main Artemis folder and execute the following command to start the build process:
. ./building/Linux/build_linux.sh\nWait for the build process to complete. This may take a few minutes depending on your system's performance. Once the process finishes, check the artemis.dist/ directory: it will contain the standalone software with the app.bin executable.
Warning
The support for the macOS compiled version of the program is temporarily limited due to a lack of machines for extensive testing. Feel free to contribute by reporting any issues you encounter by opening an Issue.
"},{"location":"build_package/#procedure_2","title":"Procedure","text":". ./building/macOS/build_macos.sh\nArtemis is an open-source project, and every contribution, no matter how small, is valuable and greatly appreciated. Don't worry about getting everything perfect; we are happy to work with you on your contribution and help you along the way. This guide will help you get started by outlining various ways you can contribute.
Spot a bug?
Please open an issue (or pull request) and let us know the problem you faced (or you're working on)
Open an Issue
Fork the repository
Create a copy of the codebase from which you can modify and submit pull requests.
Fork the repo
Ideas?
Idea for a new feature? Open an issue on the project's GitHub repository to describe your proposal.
Open an Issue
Spreading the word!
Do you like Artemis? Remember to share it with your network and your friends!
Artemis is maintained by Marco Dalla Tiezza and released under the GPLv3 license.
"},{"location":"credits/#credits","title":"Credits","text":"This question has been asked countless times, and for good reason: in many fields, machine learning (ML) has disrupted the way we solve problems, and when applied to the right field, you can get outstanding results. So why not on signals?
Well, the story dates back to at least 2017 when I started discussing it with several people on the rtl-sdr blog: at first, it seemed promising, but like many things, all that glitters is not gold. Let us proceed in order:
"},{"location":"faq/#ml-deep-learning-approach","title":"ML / Deep Learning approach","text":"A machine learning/neural network approach would not be complex (from a technical standpoint) if there were not the problem of the dataframe completeness. To be effective, neural models need to be trained on a large number of entries. The precise number can vary and strongly depends on the nature of data used for training, but commonly, numbers can be tens of thousands of entries or even more, for example. This would not be a significant concern in the case of RF signals because the various encodings that differentiate can be created artificially using for example Fldigi. To make these synthetic signals more like a real one, noise and artificial distortions can be added. However, this approach allows us to have a spectrum that ranges only over civilian, non-proprietary, and non-military signals (a little bit more than 150 out of 500, in the best-case scenario). Many efforts have been made in this field and some excellent results have been reported below:
Therefore, The main point is to have a good quality data frame to train the model; this is not always an easy task for the above reasons. Subsequently, as Stefan Scholl pointed out on his blog, similar modulations (MFSK-32 vs Olivia 16/500) can significantly decrease the effectiveness of discrimination. The quality of reception can also influence the result as well: \u00a0high SNR cannot always be an ideal point since the reception can be disrupted by interference or fading.
"},{"location":"faq/#classical-audio-analysis","title":"Classical Audio Analysis","text":"More classical methods, such as similarity recognition between audio samples (such as using Mel-frequency cepstral coefficients, for example), could be effective, albeit marginally, if applied to the 500 signals audio sample library from sigID wiki. With the same signal encoding, the content of the signal alone can affect the similarity index and, thus, the method's effectiveness. Listening to a signal with the same modulation but encoding different information can significantly decrease the accuracy of signal recognition.
"},{"location":"installation/","title":"Installation","text":"Requirements:
Artemis-Windows-x86_64-4.x.x.exe in the Assets menu from the LATEST RELEASE and follow the guided procedure to complete the installation process.On Linux, the xcb plugin is utilized to supply the essential functionality required for Qt GUI and Qt Widgets to operate on X11. On some Linux distributions the required dependencies are already met, but in many cases, you will need to install them. To install the dependencies use:
Debian-based distro (Ubuntu, Mint, Pop! OS, Kali, ...)sudo apt install libxcb-*\nDownload Artemis-Linux-x86_64-4.x.x.tar in the Assets menu from the LATEST RELEASE and extract the tarball archive in a folder of your choice.
Before running app.bin, be sure to have the executable permissions to the binary file with:
chmod 700 app.bin\nTo create a direct shortcut (in the main menu) launch the bash script in the terminal with the command:
. create_shortcut.sh\nThis script will:
Warning
The macOS support is temporarily limited!
The support for the macOS compiled version of the program is temporarily limited due to a lack of machines for extensive testing. To use Artemis on a macOS device, you have the following options:
Running Artemis directly from the source code using the Python interpreter is considered the most reliable and least problematic method. This approach ensures maximum compatibility and reduces the likelihood of encountering runtime issues. However, it is also the less practical option, as it requires the use of the terminal for the execution.
"},{"location":"run_from_source/#requirements","title":"Requirements","text":"Download and install Python (3.11 or higher) from the official website. Be sure to select the flag Add Python 3.x to PATH during the first part of the installation.
Download Artemis source code from the latest release in the GitHub repository.
Extract the downloaded archive.
Open the terminal in Artemis folder and install the required Python libraries with PIP:
pip install -r requirements.txt --user\nLaunch Artemis:
python app.py\nNote for Developers
Whenever modifications are made to any .qml file or any assets (such as images, icons, etc.), it is essential to recompile the resource.py file to ensure that the changes are reflected in the application. To achieve this, execute the following command:
pyside6-rcc ./artemis.qrc -o artemis/resources.py\nArtemis can be safely executed and/or installed in any folder (even protected ones, such as Program Files (x86) in Windows) because Artemis performs read-only operations in the BASE_DIR folder from where it runs. All the reading-writing operations (such as database ops, logging, etc.) are performed in standard folders as follow:
$USER\\AppData\\Local\\AresValley\\Artemis$USER\\AppData\\Local\\Temp~/.local/share/AresValley/Artemis/tmp~/Library/Application Support/AresValley/Artemis/tmpThe table contains 4 columns explained below.
Example
A technical explanation on how autocorrelation function works along with a practical example is reported HERE
"},{"location":"database/db_acf/#acf_id","title":"ACF_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new ACF. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_acf/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the ACF. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_acf/#value","title":"VALUE","text":"FLOAT
The autocorrelation time expressed in ms.
"},{"location":"database/db_acf/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the details about the autocorrelation value, e.g. Frame, Superframe, etc.
The table contains 4 columns explained below.
"},{"location":"database/db_bandwidth/#band_id","title":"BAND_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new bandwidth. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_bandwidth/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the bandwidth. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_bandwidth/#value","title":"VALUE","text":"INTEGER
The bandwidth in Hz expressed as an integer.
"},{"location":"database/db_bandwidth/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the purpose of the bandwidth and any other useful details.
"},{"location":"database/db_cat_label/","title":"Category Label","text":"This table contains only the name of the category/tag. The table contains 2 columns explained below.
"},{"location":"database/db_cat_label/#clb_id","title":"CLB_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new category tag. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_cat_label/#value","title":"VALUE","text":"TEXT
The name of the category/tag expressed as a string.
"},{"location":"database/db_category/","title":"Category","text":"The primary function of this table is to facilitate the classification of the signal by assigning it to its appropriate family or category. Can be used with any tag. The table contains 3 columns explained below.
"},{"location":"database/db_category/#cat_id","title":"CAT_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new category/tag. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_category/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the category. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_category/#clb_id","title":"CLB_ID","text":"INTEGER
This is a direct reference to the specific category label associated with the category. It links to the primary key of the Category Label table that holds the name of the category.
"},{"location":"database/db_frequency/","title":"Frequency","text":"The table contains 4 columns explained below.
"},{"location":"database/db_frequency/#freq_id","title":"FREQ_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new frequency. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_frequency/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the frequency. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_frequency/#value","title":"VALUE","text":"INTEGER
The freqeuncy in Hz expressed as an integer.
"},{"location":"database/db_frequency/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the purpose of the bandwidth and any other useful details.
"},{"location":"database/db_info/","title":"Info","text":"This is the database meta table and contains 4 columns explained below.
"},{"location":"database/db_info/#name","title":"NAME","text":"TEXT
This is the name of the database.
"},{"location":"database/db_info/#data","title":"DATA","text":"TEXT
The creation date when the database has been initialised.
"},{"location":"database/db_info/#version","title":"VERSION","text":"INTEGER
A simple integer to denote the database version.
"},{"location":"database/db_info/#editable","title":"EDITABLE","text":"INTEGER
This field should serve as a writing protection on the database.
This is the location where the signal is distributed/received. Avoid the usage of the precise location of the TX station or very small town (very rare). It's a good habit to use nations/continents or special location (like Worldwide). The table contains 4 columns explained below.
INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new location. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_location/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the location. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_location/#value","title":"VALUE","text":"TEXT
The location expressed as a string.
"},{"location":"database/db_location/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain further details about the location.
"},{"location":"database/db_mode/","title":"Mode","text":"This field reports the way how a signals has been decoded during the reception. The table contains 4 columns explained below.
"},{"location":"database/db_mode/#mod_id","title":"MOD_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new mode. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_mode/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the modulation. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_mode/#value","title":"VALUE","text":"TEXT
The mode expressed as a string.
"},{"location":"database/db_mode/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the purpose of the mode and any other useful details.
"},{"location":"database/db_modulation/","title":"Modulation","text":"Modulation refers to the method by which information is encoded into the main signal (carrier). This process involves altering various properties of the carrier signal, such as amplitude, frequency, or phase. Multiple modulation techniques can be employed, and a TX station has the capability to utilize different modulation schemes. The table contains 4 columns explained below.
"},{"location":"database/db_modulation/#mdl_id","title":"MDL_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a new modulation. It is auto-incrementing and is not replaced in the event of deletion.
"},{"location":"database/db_modulation/#sig_id","title":"SIG_ID","text":"INTEGER
This is a direct reference to the specific signal associated with the modulation. It links to the primary key of the Signals table that holds detailed information about the signals.
"},{"location":"database/db_modulation/#value","title":"VALUE","text":"TEXT
The modulation expressed as a string.
"},{"location":"database/db_modulation/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the purpose of the modulation and any other useful details.
"},{"location":"database/db_overview/","title":"Database","text":"With the release of Artemis 4, we have made a significant upgrade in our data management system by transitioning from a CSV file to a full relational SQL database. This change brings a multitude of advantages that enhance the efficiency, scalability, and reliability of our system. In the following sections, we will explore, table by table, the structure of the new database.
"},{"location":"database/db_signals/","title":"Signals","text":"This is the main table and contains 4 columns explained below.
"},{"location":"database/db_signals/#sig_id","title":"SIG_ID","text":"INTEGER
This is a unique identification number for each entry that is assigned during the creation of a signal. It is auto-incrementing and is not replaced in the event of signal deletion.
"},{"location":"database/db_signals/#name","title":"NAME","text":"TEXT
The name of the signal. A simple string that describes in short the analyzed signal. Special characters are allowed.
"},{"location":"database/db_signals/#description","title":"DESCRIPTION","text":"TEXT
The short description is used to explain the purpose of the signal and some other useful details.
Tip
The DESCRIPTION field supports Markdown, a simple markup language for creating rich text using plain text. Headers, emphasis, lists, links, code blocks and many more features for advanced text formtting. Markdown Basic Syntax
"},{"location":"database/db_signals/#url","title":"URL","text":"TEXT
The sigidwiki (SigID) URL of the selected signal. This is a direct connection to the online database where further details of the signal are collected.
Info
Internal Use Only This field is for the SigID database and not intended for user viewing or editing. Personal URLs can be stored in the signal description.
"},{"location":"database/sigid/","title":"SigID Wiki Database","text":"Artemis serves as a valuable resource for both personal signal collection and leveraging a vast repository of pre-identified signals. This software application allows users to curate their own collections, but its true strength lies in its integration with a comprehensive database of known signals. This database is directly sourced from the Signal Identification Wiki, an open-source resource collaboratively maintained by a global community of radio enthusiasts.
Database Revision
For quality control purposes, the database undergoes a rigorous review process before integration into Artemis. This review adheres to established guidelines, ensuring the accuracy and completeness of the information presented to users. The specifics of this review process are outlined in the following section.
"},{"location":"database/sigid/#modulation","title":"Modulation","text":"A good practise (reported also on ) is to write the primary type of modulation (if known) and not all the possible variants. A practical example is reported on Signal Identification Wiki: there is no need to write 8-PSK or QPSK, PSK is enough. The Artemis SigID database is provided without any modulation variants included. The recognized modulations are listed below:
"},{"location":"database/sigid/#analog","title":"Analog","text":"Locations are either countries or special token (Worldwide, Europe, etc.) . Precise location of the TX station, towns and cities are converted to their respective countries.
Synoptic maps of the solar surface are drawn each day by SWPC forecasters, providing forecasters with a broad outline of solar surface features. These maps were started on June 2, 1972 and have been produced daily since then.
Source
The Solar Synoptic Analysis is courtesy of the Space Weather Prediction Center (SWPC) part of the National Oceanic and Atmospheric Administration (NOAA), located in Boulder, Colorado.
"},{"location":"space_weather/SSA/#how-to-read","title":"How to Read","text":""},{"location":"space_weather/SSA/#active-regions","title":"Active Regions","text":"Active regions are localized magnetic fields on the Sun. Areas with strong or intense magnetic fields provide energy for solar flares and coronal mass ejections (CMEs), so accurate forecasting of space weather activity requires an accurate picture of these regions.. Active regions are given official numbers by SWPC, and the drawings include the probabilities of C, M, and X class flares for the next 24 hours associated with each active region, along with a proton event probability.
"},{"location":"space_weather/SSA/#coronal-holes","title":"Coronal Holes","text":"Coronal holes are single polarity magnetic regions that are the source of high speed solar winds which drive magnetospheric activity. Coronal holes are the most common cause of geomagnetic storms. Coronal holes have historically been identified from He I 10830A ground-based observations. The boundaries of coronal holes are shown on the synoptic drawings as lines with hash marks on the coronal hole side of the boundary line.
"},{"location":"space_weather/SSA/#neutral-lines","title":"Neutral Lines","text":"Large magnetic field structures of one magnetic polarity have a \u2018neutral line\u2019 at the boundary of the different magnetic polarities of the fields. Neutral lines are associated with flaring in active regions, and filaments/prominences are often associated with the neutral lines on a quiet sun. Neutral lines appear as dashed lines on the synoptic drawings and the forecaster indicates the polarity of the magnetic field on either side of the neutral line with + (positive) and \u2013 (negative) signs.
"},{"location":"space_weather/SSA/#plages","title":"Plages","text":"Plages make up most of an Active Region, and appear bright in conjunction with the dark sunspots. Plages have strong magnetic fields but disorganized magnetic fields, unlike the highly organized fields of sunspots. In the synoptic drawings, plages are colored red. It is quite normal to have regions of plage with no sunspots, which do not receive an official number since they are not considered active regions and are unlikely to produce solar flares. Plage regions are the chief source of UV variability from the sun, however.
"},{"location":"space_weather/SSA/#filaments-and-prominences","title":"Filaments and Prominences","text":"Highly-stable regions of high density gas in the low density corona are called filaments. When these occur near the limb and can be seen protruding from the corona, often in spectacular fashion, they are called prominences. When they erupt they can be a geomagnetic storm threat, but the eruptions are usually slow and don\u2019t often drive large storms. The filaments and prominences are drawn as outlines with hash marks.
"},{"location":"space_weather/SSA/#solar-coordinates","title":"Solar Coordinates","text":"Spot groups are labeled with their assigned NOAA SWPC number. Underneath that number are four probability numbers (from 1 to 100 %) for C-class flares, M-class flares, X-class flares, and energetic proton events.
"},{"location":"space_weather/SSA/#coronal-hole-labeling","title":"Coronal Hole Labeling","text":"Coronal holes are labeled with their assigned number. Underneath that number is a plus or minus sign representing the polarity of the coronal hole. Beside that figure is a number from 1 to 4 representing confidence of coronal hole analysis (4=good; 3=fair; 2=poor; 1=uncertain).
"},{"location":"space_weather/aurora/","title":"Aurora","text":"This short-term aurora forecast predicts its location and intensity over the next 30 to 90 minutes, based on the OVATION model. The lead time of the forecast corresponds to the duration it takes for the solar wind to travel from the L1 observation point to Earth.
Auroras indicate current geomagnetic storm conditions and provide situational awareness for various technologies: for example, they directly affect HF radio communication and GPS/GNSS satellite navigation and are related to ground-induced currents impacting electric power transmission.
For many people, the aurora is a beautiful nighttime phenomenon that is worth traveling to arctic regions just to observe. It is the only way for most people to actually experience space weather.
"},{"location":"space_weather/current/","title":"Current","text":""},{"location":"space_weather/current/#1-kp-index","title":"1. Kp Index","text":"The K index is a number (from 0 to 9) that shows how much Earth's magnetic field is disturbed. A K index of 1 means things are calm, while a K index of 5 or higher indicates a geomagnetic storm. These disturbances are measured with magnetometers that track changes in Earth's magnetic field every three hours. The K itself comes from a German word \"Kennziffer\" meaning \"characteristic digit\". To get a big picture of what's happening around the world, an official planetary Kp index is calculated. This is done by averaging the K indices from a special network of 13 geomagnetic observatories located around the globe at mid-latitudes.
Index Activity Level High Latitudes Low Latitudes Possible Source Kp 0 Inactive Weak & slow aurora possible Aurora extremely unlikely Small influx of particles due to some reconnections mostly at the magnetotail Kp 1 Very Quiet Weak & slow aurora likely Aurora very unlikely Vide supra Kp 2 Quiet Moderate auroral display Aurora unlikely Vide supra Kp 3 Unsettled Active auroral display, sporadic substorm possible Weak aurora display possible Coronal hole sending fast winds or remains after days of storming, enhanced solar wind Kp 4 Active Active auroral display, multiple sporadic substorms possible Weak Aurora Display Possible Vide supra Kp 5 Minor Storm (G1) Very active auroral display, multiple substorms likely Aurora display likely Coronal hole sending fast winds or coronal mass ejection (CME), enhanced solar wind Kp 6 Moderate Storm (G2) Strong auroral display, longer substorms Active auroral display very likely Vide supra Kp 7 Strong Storm (G3) Very strong auroral display Strong auroral display extremely likely Large CMEs caused by solar storms or flares, very enhanced solar wind with strong shock wave Kp 8 Severe Storm (G4) Extremely strong aurora, long periods of substorming Strong auroral display extremely likely Vide supra Kp 9 Extreme Storm (G5) Extremely strong aurora, long periods of substorming Very strong auroral display, overhead aurora possible Super CMEs, Carrington-class events, devastating solar wind with extreme shock waves"},{"location":"space_weather/current/#2-ap-index","title":"2. Ap Index","text":"The A index represents the three-hourly equivalent amplitude of geomagnetic activity at a specific magnetometer station, derived from the station-specific K index. Due to the quasi-logarithmic nature of the K-scale in relation to magnetometer fluctuations, directly averaging a set of K indices is not really meaningful. Instead each K is converted back into a linear scale. The Ap index is determined by averaging the eight daily Ap values (3-hour) and using the same stations grid explained for the Kp index in the previous section. This provides a measure of geomagnetic activity for a specific day. Days with higher levels of geomagnetic activity correspond to higher daily Ap values.
"},{"location":"space_weather/current/#3-noaa-space-weather-scale","title":"3. NOAA Space Weather Scale","text":""},{"location":"space_weather/current/#geomagnetic-storm","title":"Geomagnetic Storm","text":"G5 (Extreme)Power systems: Widespread voltage control problems and protective system problems can occur, some grid systems may experience complete collapse or blackouts. Transformers may experience damage.
Spacecraft operations: May experience extensive surface charging, problems with orientation, uplink/downlink and tracking satellites.
Other systems: Pipeline currents can reach hundreds of amps, HF (high frequency) radio propagation may be impossible in many areas for one to two days, satellite navigation may be degraded for days, low-frequency radio navigation can be out for hours, and aurora has been seen as low as Florida and southern Texas (typically 40\u00b0 geomagnetic lat.).
G4 (Severe)Power systems: Possible widespread voltage control problems and some protective systems will mistakenly trip out key assets from the grid.
Spacecraft operations: May experience surface charging and tracking problems, corrections may be needed for orientation problems.
Other systems: Induced pipeline currents affect preventive measures, HF radio propagation sporadic, satellite navigation degraded for hours, low-frequency radio navigation disrupted, and aurora has been seen as low as Alabama and northern California (typically 45\u00b0 geomagnetic lat.).
G3 (Strong)Power systems: Voltage corrections may be required, false alarms triggered on some protection devices.
Spacecraft operations: Surface charging may occur on satellite components, drag may increase on low-Earth-orbit satellites, and corrections may be needed for orientation problems.
Other systems: Intermittent satellite navigation and low-frequency radio navigation problems may occur, HF radio may be intermittent, and aurora has been seen as low as Illinois and Oregon (typically 50\u00b0 geomagnetic lat.).
G2 (Moderate)Power systems: High-latitude power systems may experience voltage alarms, long-duration storms may cause transformer damage.
Spacecraft operations: Corrective actions to orientation may be required by ground control; possible changes in drag affect orbit predictions.
Other systems: HF radio propagation can fade at higher latitudes, and aurora has been seen as low as New York and Idaho (typically 55\u00b0 geomagnetic lat.).
G1 (Minor)Power systems: Weak power grid fluctuations can occur.
Spacecraft operations: Minor impact on satellite operations possible.
Other systems: Migratory animals are affected at this and higher levels; aurora is commonly visible at high latitudes (northern Michigan and Maine).
"},{"location":"space_weather/current/#solar-radiation-storms","title":"Solar Radiation Storms","text":"S5 (Extreme)Biological: Unavoidable high radiation hazard to astronauts on EVA (extra-vehicular activity); passengers and crew in high-flying aircraft at high latitudes may be exposed to radiation risk.
Satellite operations: Satellites may be rendered useless, memory impacts can cause loss of control, may cause serious noise in image data, star-trackers may be unable to locate sources; permanent damage to solar panels possible.
Other systems: Complete blackout of HF (high frequency) communications possible through the polar regions, and position errors make navigation operations extremely difficult.
S4 (Severe)Biological: Unavoidable radiation hazard to astronauts on EVA; passengers and crew in high-flying aircraft at high latitudes may be exposed to radiation risk.
Satellite operations: May experience memory device problems and noise on imaging systems; star-tracker problems may cause orientation problems, and solar panel efficiency can be degraded.
Other systems: Blackout of HF radio communications through the polar regions and increased navigation errors over several days are likely.
S3 (Strong)Biological: Radiation hazard avoidance recommended for astronauts on EVA; passengers and crew in high-flying aircraft at high latitudes may be exposed to radiation risk.
Satellite operations: Single-event upsets, noise in imaging systems, and slight reduction of efficiency in solar panel are likely.
Other systems: Degraded HF radio propagation through the polar regions and navigation position errors likely.
S2 (Moderate)Biological: Passengers and crew in high-flying aircraft at high latitudes may be exposed to elevated radiation risk.
Satellite operations: Infrequent single-event upsets possible.
Other systems: Small effects on HF propagation through the polar regions and navigation at polar cap locations possibly affected.
S1 (Minor)Biological: None.
Satellite operations: None.
Other systems: Minor impacts on HF radio in the polar regions.
"},{"location":"space_weather/current/#radio-blackouts","title":"Radio Blackouts","text":"R5 (Extreme)HF Radio: Complete HF (high frequency**) radio blackout on the entire sunlit side of the Earth lasting for a number of hours. This results in no HF radio contact with mariners and en route aviators in this sector.
Navigation: Low-frequency navigation signals used by maritime and general aviation systems experience outages on the sunlit side of the Earth for many hours, causing loss in positioning. Increased satellite navigation errors in positioning for several hours on the sunlit side of Earth, which may spread into the night side.
*GOES X-ray peak brightness by class and by flux (measured in the 0.1-0.8 nm range, in W\u00b7m-2)
R4 (Severe)HF Radio: HF radio communication blackout on most of the sunlit side of Earth for one to two hours. HF radio contact lost during this time.
Navigation: Outages of low-frequency navigation signals cause increased error in positioning for one to two hours. Minor disruptions of satellite navigation possible on the sunlit side of Earth.
*GOES X-ray peak brightness by class and by flux (measured in the 0.1-0.8 nm range, in W\u00b7m-2)
R3 (Strong)HF Radio: Wide area blackout of HF radio communication, loss of radio contact for about an hour on sunlit side of Earth.
Navigation: Low-frequency navigation signals degraded for about an hour.
*GOES X-ray peak brightness by class and by flux (measured in the 0.1-0.8 nm range, in W\u00b7m-2)
R2 (Moderate)HF Radio: Limited blackout of HF radio communication on sunlit side of the Earth, loss of radio contact for tens of minutes.
Navigation: Degradation of low-frequency navigation signals for tens of minutes.
*GOES X-ray peak brightness by class and by flux (measured in the 0.1-0.8 nm range, in W\u00b7m-2)
R1 (Minor)HF Radio: Weak or minor degradation of HF radio communication on sunlit side of the Earth, occasional loss of radio contact.
Navigation: Low-frequency navigation signals degraded for brief intervals.
*GOES X-ray peak brightness by class and by flux (measured in the 0.1-0.8 nm range, in W\u00b7m-2)
"},{"location":"space_weather/current/#4-x-ray-solar-activity","title":"4. X-Ray Solar Activity","text":"This is a summary of the X-Ray Flare Class. Large solar X-ray flares can change the Earth\u2019s ionosphere, which blocks high-frequency (HF) radio transmissions on the sunlit side of the Earth. Solar flares are also associated with Coronal Mass Ejections (CMEs) which can ultimately lead to geomagnetic storms. SWPC sends out space weather alerts at the M5 level. Some large flares are accompanied by strong radio bursts that may interfere with other radio frequencies and cause problems for satellite communication and radio navigation (GPS).
Class Peak Strength (W/m2) Effects on Earth B I < 10-6 Too small to harm Earth C 10-6 \u2264 I < 10-5 Small with few noticeable consequences M 10-5 \u2264 I < 10-4 Brief radio blackouts in polar regions, minor radiation storms X I \u2265 10-4 Planet-wide radio blackouts, long-lasting radiation storms"},{"location":"space_weather/current/#5-rf-propagation","title":"5. RF Propagation","text":""},{"location":"space_weather/current/#maximum-usable-frequency","title":"Maximum Usable Frequency","text":"In radio transmission, the maximum usable frequency (MUF) is the highest frequency that can be effectively used for communication between two locations on Earth by reflecting off the ionosphere (via skywave or skip) at a given time, regardless of the transmitter's power. This measurement is particularly valuable for shortwave transmissions.
"},{"location":"space_weather/current/#earth-moon-earth","title":"Earth-Moon-Earth","text":"Earth\u2013Moon\u2013Earth communication (EME), commonly referred to as Moon bounce, is a radio communication method in which radio waves are transmitted from an Earth-based station, reflected off the Moon's surface, and then received back on Earth. The value gives the probability of a succesfull connection.
"},{"location":"space_weather/current/#meteor-scatter","title":"Meteor Scatter","text":"Meteor burst communications (MBC), also known as meteor scatter (MS) communications, is a radio propagation technique that uses the ionized trails created by meteors entering the atmosphere to establish brief communication links between radio stations up to 2,250 kilometers (1,400 miles) apart. This can involve either forward-scatter or back-scatter of the radio waves. Like EME, the value gives the probability of a succesfull connection.
"},{"location":"space_weather/current/#sporadic-e","title":"Sporadic-E","text":"Report of the latest E-skip spots on 50, 70 & 144 MHz by DXrobot
Sporadic E (Es or SpE) is a rare type of radio propagation that uses a lower part of the Earth's ionosphere, which typically doesn't refract radio waves. It reflects signals off small \"clouds\" in the E region at altitudes of 95-150 km (50-100 miles). Unlike the regular F region skywave propagation, which depends on daily cycles of ionized layers from UV light, Sporadic E uses transient ionized patches. This allows for occasional long-distance VHF communication, usually during the six weeks around the summer solstice, beyond the normal line-of-sight range.
"},{"location":"space_weather/current/#aurora-spots","title":"Aurora Spots","text":"Report of the latest aurora spots on 50, 70 & 144 MHz by DXrobot
Auroral propagation, or auroral backscatter, is a form of radio propagation that occurs during an auroral event, affecting VHF and UHF communications. Increased ionization in the E layer of the ionosphere reflects signals at much higher frequencies than usual, enabling communication up to 1000 MHz, though 500 MHz is more common. Signals are directed towards the auroral region and reflected back, but they are often distorted due to particle movement (the signal is roughly Doppler shifted of 1 kHz at around 150 MHz as the electrons stream down).
"},{"location":"space_weather/current/#expected-hf-noise","title":"Expected HF Noise","text":"This is just the expected noise in HF based on the current Space Weather conditions.
"},{"location":"space_weather/current/#6-report-age","title":"6. Report Age","text":"Poseidon Daemon is in charge of parse all the necessary data used for the Space Weather module. The data of the last generated report is written here.
"},{"location":"space_weather/drap/","title":"DRAP","text":"The D-Region Absorption Product (DRAP) evaluates the effects of solar X-ray flux and solar energetic particle (SEP) events on HF radio communication. Long-distance communications using high frequency (HF) radio waves (3 - 30 MHz) rely on signal reflection in the ionosphere. Typically, radio waves reflect near the peak of the F2 layer (~300 km altitude), but during their journey to and from this peak, the signals experience attenuation due to absorption by the intervening ionosphere.
The D-Region Absorption Prediction model provides guidance to understand the degradation and blackouts of HF radio communications that can result from these conditions.
"},{"location":"space_weather/forecasts/","title":"Forecasts","text":""},{"location":"space_weather/forecasts/#1-forecast-summary","title":"1. Forecast Summary","text":"Geomagnetic activity, Solar Radiation Storms and Radio Blackouts probable events (in the next 3 days) are described in this section.
"},{"location":"space_weather/forecasts/#2-3-day-kp-index","title":"2. 3-Day Kp Index","text":"This is a 3 day projection of the Kp index.
"},{"location":"space_weather/forecasts/#3-events-probability","title":"3. Events Probability","text":"The probability (in percentage) of different events that can take place and generate some important conditions for RF propagation. All the event are explained here.
Info
Geomagnetic Activity has two percentual value per day: the left one refers to high-latitude location and the right one is for middle-latitude locations.
"},{"location":"space_weather/imagers/","title":"Sun Imagers","text":""},{"location":"space_weather/imagers/#atmospheric-imagery-assembly","title":"Atmospheric Imagery Assembly","text":""},{"location":"space_weather/imagers/#94-a","title":"94 \u00c5","text":"This channel (as well as AIA 131) is designed to study solar flares. It measures extremely hot temperatures around 6 million Kelvin (10.8 million F). It can take images every 2 seconds (instead of 10) in a reduced field of view in order to look at flares in more detail.
This channel (as well as AIA 094) is designed to study solar flares. It measures extremely hot temperatures around 10 million K (18 million F), as well as cool plasmas around 400,000 K (720,000 F). It can take images every 2 seconds (instead of 10) in a reduced field of view in order to look at flares in more detail.
This channel is especially good at showing coronal loops - the arcs extending off of the Sun where plasma moves along magnetic field lines. The brightest spots seen here are locations where the magnetic field near the surface is exceptionally strong.
This channel highlights the outer atmosphere of the Sun - called the corona - as well as hot flare plasma. Hot active regions, solar flares, and coronal mass ejections will appear bright here. The dark areas - called coronal holes - are places where very little radiation is emitted, yet are the main source of solar wind particles.
This channel is especially good at showing areas where cooler dense plumes of plasma (filaments and prominences) are located above the visible surface of the Sun. Many of these features either can't be seen or appear as dark lines in the other channels. The bright areas show places where the plasma has a high density.
This channel (as well as AIA 211) highlights the active region of the outer atmosphere of the Sun - the corona. Active regions, solar flares, and coronal mass ejections will appear bright here. The dark areas - or coronal holes - are places where very little radiation is emitted, yet are the main source of solar wind particles.
This channel (as well as AIA 1700) often shows a web-like pattern of bright areas that highlight places where bundles of magnetic fields lines are concentrated. However, small areas with a lot of field lines will appear black, usually near sunspots and active regions.
This channel (as well as AIA 1600) often shows a web-like pattern of bright areas that highlight places where bundles of magnetic fields lines are concentrated. However, small areas with a lot of field lines will appear black, usually near sunspots and active regions.
Magnetograms show maps of the magnetic field on the Sun\u2019s surface. The HMI instrument uses the Zeeman effect to measure the intensity of the magnetic field component along the line of sight by making use of the circularly polarized spectral line. The color chart of the magnetic field along the line of sight is designed to visually show both high and low values. Intensities less than 24G are shades of gray. Positive values of the field are green and blue. Negative values are yellow and red. Regions with a weak field appear mainly in yellow or green. Progressively positive values range from dark green to light green (at 236 G). Negative values range from light yellow to orange (at -236G). There is a strong discontinuity in the coloration at 236G. Positive or negative sunspots and other regions with an intense field appear blue or red with dark umbrae. There are 254 colors arranged symmetrically around 0. The 127 positive values include 2 grays tending toward dark, 13 greens toward light, and 110 blues toward dark. The 127 negative values include 2 grays tending toward light, 18 yellows toward dark, and 107 reds toward dark. Nominally, each color indicates a range of about 11.81 G, and the coloration altogether spans the range between -1500 G and 1500 G
"},{"location":"space_weather/imagers/#intensitygram","title":"Intensitygram","text":"HMI samples the Fe I absorption line at 6173.3 \u00c5 at six points, assuming that the \"pure\" profile of the Fe I line is Gaussian and the transmission profiles are delta functions, the first and second Fourier coefficients of the Fe I line profile can be calculated, and Doppler velocity estimation can be performed. An estimate of the intensity in the continuum is obtained by \"reconstructing\" the solar line from the Doppler offset and the thickness and depth of the line.
"},{"location":"space_weather/imagers/#dopplergram","title":"Dopplergram","text":"HMI camera 2 takes 72 images to construct a single Doppler diagram. Six images are taken at six positions across the spectral line at 6173.3 \u00c5. Each image is taken in two polarization states, circularly polarized to the right (RCP or Stokes I-V) and circularly polarized to the left (LCP or Stokes I+V). Assuming that the absorption line is Gaussian and the transmission profiles of the HMI filter are delta functions, Fourier coefficients are calculated and then used to estimate the magnetic field B along the line of sight.
"},{"location":"space_weather/imagers/#large-angle-and-spectrometric-coronagraph","title":"Large Angle and Spectrometric Coronagraph","text":""},{"location":"space_weather/imagers/#lasco-c1-not-available","title":"LASCO C1 (NOT AVAILABLE)","text":"A Fabry\u2013P\u00e9rot interferometer coronagraph imaging from 1.1 to 3 solar radii, non-functional since the 24 June 1998 SOHO Mission Interruption
"},{"location":"space_weather/imagers/#lasco-c2-orange","title":"LASCO C2 (orange)","text":"A white light coronagraph imaging from 1.5 to 6 solar radii
"},{"location":"space_weather/imagers/#lasco-c3-blue","title":"LASCO C3 (blue)","text":"A white light coronagraph imaging from 3.7 to 30 solar radii
"}]}