2b:null 2c:["$","title",null,{"children":"GPS jamming around Kaliningrad | Open Aviation | Observable"}] 31:T7be,jamming_map = function ( data, { scale = 1, caption = undefined, title = undefined } ) { const bin = d3.hexbin().radius(radius)( Array.from(data, ({ longitude, latitude, icao24, HPL }) => Object.assign(projection([longitude, latitude]), { icao24, HPL }) ) ); return Plot.carto({ style: "background: #d7f0f6", width, height, caption, title, projection, marks: [ //Plot.feature(d3.geoGraticule10(), { strokeWidth: 0.25 }), Plot.features(countries.features, { title: (d) => d.properties.sovereignt, stroke: "black", strokeWidth: 0.5, fill: "#f0f0f0" }), Plot.dot(bin, { x: "x", y: "y", r: (bin) => Math.min(15, new Set(bin.map((d) => d.icao24)).size), symbol: hexagon, // fillOpacity: 0.8, fill: (bin) => new Set(bin.filter((d) => d.HPL > 200).map((d) => d.icao24)).size / new Set(bin.map((d) => d.icao24)).size, stroke: "white", strokeWidth: 0.5 }), Plot.features(countries.features, { title: (d) => d.properties.sovereignt, stroke: "black", strokeWidth: 0.25 // strokeDasharray: [3, 2] }), Plot.text(bin, { x: "x", y: "y", text: (bin) => `${ new Set(bin.filter((d) => d.HPL > 200).map((d) => d.icao24)).size }/${new Set(bin.map((d) => d.icao24)).size}`, fill: "black", stroke: "white", strokeWidth: 3 }), Plot.label(country_labels, { lonLat: (d) => d.coordinates, fill: "steelblue", text: (d) => d.properties.name, textAnchor: "middle", fontSize: 14, dx: 7, dy: 16, halo: true }) ], r: { range: [0, radius - 0.3] }, color: { scheme: "reds", domain: [0, 100], //legend: true, percent: true, label: "HPL > 200 (%)" } }); }32:[{"id":"7e0b084d6249ccd22fa262527ec7bc4ca6f8158e0e2da48015800f470b97ccd1608497eb6e346c403f7fedbda9506d7015fb2f5dcceb03bdffbb54cf563bbd14","href":"https://static.observableusercontent.com/files/7e0b084d6249ccd22fa262527ec7bc4ca6f8158e0e2da48015800f470b97ccd1608497eb6e346c403f7fedbda9506d7015fb2f5dcceb03bdffbb54cf563bbd14","name":"kaliningrad_jamming.parquet","type":"application/octet-stream","lastModified":1647291977667.701,"size":9448202}] 2f:{"id":"fc6ac0a301122cae","slug":"gps-jamming","title":"GPS jamming around Kaliningrad","thumbnail":"57b0f0c0cc442d35271fcb41e388c2aa03aa4e133cdefeb1e3ecffc9ea0e78da","access_level":"public","create_time":"$D2022-03-14T09:03:31.078Z","update_time":"$D2022-11-05T13:26:33.717Z","view_time":null,"first_public_time":"$D2022-03-15T09:36:01.227Z","fork":false,"stars":16,"starred":false,"owner":{"type":"team","id":"b72632526f8c9afb","login":"openaviation","name":"Open Aviation","avatar_url":"https://avatars-next.observableusercontent.com/785c72955c757d5479584b620b48d5133f1f6ac3b42119b2b2445045440f0b09","tier":"starter_2024"},"version":599,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"0b2e8d88aeec5ab4","login":"xoolive","name":"Xavier Olive","avatar_url":"https://avatars-next.observableusercontent.com/e055a445877c5a8ee2da134a257760536c2d1ee2fcd43f3aaf3f40db54e13733","tier":null},{"type":"individual","id":"45a379fcfcb14253","login":"fil","name":"Fil","avatar_url":"https://avatars-next.observableusercontent.com/d5b1777907117a2bdf2a07eb98600d7a9beb21639fde42b9753e95c88c7731a6","tier":null}],"members":[{"type":"team","id":"b72632526f8c9afb","login":"openaviation","name":"Open Aviation","avatar_url":"https://avatars-next.observableusercontent.com/785c72955c757d5479584b620b48d5133f1f6ac3b42119b2b2445045440f0b09","tier":"starter_2024","role":"editor"},{"type":"individual","id":"0b2e8d88aeec5ab4","login":"xoolive","name":"Xavier Olive","avatar_url":"https://avatars-next.observableusercontent.com/e055a445877c5a8ee2da134a257760536c2d1ee2fcd43f3aaf3f40db54e13733","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"subscribed":null,"forks":6,"collection":{"id":"720ac08ffd66c964","slug":"open-aviation","title":"Visualizing Aviation","owner":{"id":"b72632526f8c9afb","login":"openaviation","name":"Open Aviation"}},"type":"notebook","body":{"title":"GPS jamming around Kaliningrad","cells":[{"id":0,"value":"

series: impact of the ukraine invasion on commercial aviation

\n# GPS jamming around Kaliningrad","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":275,"value":"1. [How flights between Europe and Eastern Asia got disrupted](https://observablehq.com/@espinielli/war-in-ukraine-airspace-blockade)\n2. [Flying to Kaliningrad during the Russian flight ban](https://observablehq.com/@xoolive/flying-to-kaliningrad)\n3. **[GPS jamming around Kaliningrad](https://observablehq.com/@xoolive/gps-jamming)**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":383,"value":"Early in March, a lot of aircraft in the Baltic countries and Finland have been reporting GPS jamming issues. Aircraft use the global positioning system (GPS) satellites —in addition to complex inertial systems— both to locate themselves and for navigation purposes. Geolocation is based on electromagnetic signals received from at least 4 GPS satellites on specific frequencies. Jamming consists in emitting noise (or false information) on those frequencies in order to confuse GPS systems signals, avoid tracking or as part of an electronic warfare strategy.\n\nThe following map displays a GPS jamming situation around the Kaliningrad exclave on March 5th, 2022. **Darker cells mean that many aircraft were impacted by GPS jamming**. Smaller cells means few aircraft have been reported in that area: note that European aircraft are not allowed by Russia to fly over the Kaliningrad exclave—in retaliation for the Russian flights ban over European airspace starting on February 28th.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":368,"value":"jamming_map(\n data.filter((x) => x.timestamp > 1646438400000),\n { caption: \"March 5th 2022, data from The OpenSky Network\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":356,"value":"## Background\n\nThis notebook is actually inspired by a series of tweets by [John Wiseman](https://twitter.com/lemonodor) who is making a great job at monitoring GNSS interference based on ADS-B data.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":359,"value":"html`

I thought making maps of GPS/GNSS interference might turn out boring. But 3 days ago suddenly the Baltic (Poland, Lithuania, Latvia, Kaliningrad) started having some of the most significant interference on the planet, after weeks of nothing unusual. Why now? pic.twitter.com/Hnwh6Hgjmk
— John Wiseman (@lemonodor) March 7, 2022

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":375,"value":"Aircraft compute their positions using different systems, including GPS and inertial systems for navigation purposes, then most aircraft transmit their position using radio signals using a protocol called ADS-B (for Automatic Dependent Surveillance–Broadcast). Some of the fields they broadcast are related to the uncertainty they have on their position.\n\nOne of these uncertainty fields (there are more, see [here](https://mode-s.org/decode/content/ads-b/7-uncertainty.html)), the Horizontal protection limit (HPL, in meters) reflects the uncertainty the aircraft has on its GPS positions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":271,"value":"Inputs.table(data, {\n width: { timestamp: \"20%\" },\n sort: \"timestamp\",\n layout: \"auto\",\n columns: [\n \"timestamp\",\n \"icao24\",\n \"callsign\",\n \"latitude\",\n \"longitude\",\n \"altitude\",\n \"HPL\"\n ],\n format: {\n timestamp: (x) => new Date(x).toISOString(),\n icao24: (x) => html`

${x}`,\n    callsign: (x) => html`${x}`\n  }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":407,"value":"In this map, we compute an hexagonal grid around the area where we got the data, and **count the number of distinct aircraft** displaying an HPL value above a given threshold (here 200m, actually 185m for 0.1 nautical mile).\n\n- At the center of each cell: we display the **number of impacted aircraft** followed by the **total number of aircraft** flying inside that cell.\n- The **color** is proportional to that ratio: the darker the cell, the higher the noise.\n- The hexagons which have less than 15 aircraft are shown with a **smaller size** as they are not as significant.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":433,"value":"\nFor comparison purposes, **the same day in February** also shows aircraft subject to various sources of noise impacting their GPS performance, but there is **no clear sign of intention to harm**.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":331,"value":"jamming_map(\n  data.filter((x) => x.timestamp < 1646438400000),\n  { caption: \"February 5th 2022, data from The OpenSky Network\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":446,"value":"## Data sources\n\nFlight trajectories come from [The OpenSky Network](https://www.opensky-network.org), a non-profit organisation based in Switzerland. The OpenSky Network consists of a multitude of sensors connected to the Internet by volunteers, industrial supporters, and academic/governmental organizations. All collected raw data is archived in a large historical database. The database is primarily used by researchers from different areas to analyze and improve air traffic control technologies and processes.\n\nTheir database contains all raw messages sent by aircraft, which enabled us to decode all uncertainty information which are usually not provided by ADS-B data providers. Decoding was performed offline with the Python [pyModeS](https://github.com/junzis/pyModeS) library. The selected data were then exported as a parquet file.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":428,"value":"*Boring zone*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":341,"value":"a = new Date(\"2022-03-05 00:00Z\").getTime()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":155,"value":"radius = 22","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"height = 700","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":66,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":508,"value":"// import {country_labels} from \"@xoolive/flying-to-kaliningrad\"\ncountry_labels = [\n  [\"Estonia\", 25.720882,58.788955],\n  [\"Kaliningrad\", 20.4, 55.0],\n  [\"Latvia\", 24.860902,56.973568],\n  [\"Lithuania\", 23.859301,55.508246],\n  [\"Belarus\", 28.163753,53.3],\n  [\"Russia\", 30.088763,57.056650],\n  [\"Finland\", 24.820690,60.986535],\n  [\"Sweden\", 15.055561,58.24],\n  [\"Poland\", 20.153990,53.791018]\n].map((x)=>Object({type: \"Point\", coordinates:  [x[1], x[2]], properties: {'name': x[0]}}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"projection = d3\n  .geoConicConformal()\n  .rotate([-20, -56])\n  .fitExtent(\n    [\n      [radius * 2, radius * 2],\n      [width - radius * 2, height - radius * 2]\n    ],\n    {\n      type: \"MultiPoint\",\n      coordinates: [\n        [10, 50],\n        [20, 50],\n        [30, 62]\n      ]\n    }\n  )\n  .clipExtent([\n    [-2, -2],\n    [width+2, height+2]\n  ])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":307,"value":"data = aq\n  .fromArrow(\n    await pq.readParquet(\n      new Uint8Array(\n        await FileAttachment(\"kaliningrad_jamming.parquet\").arrayBuffer()\n      )\n    )\n  )\n  .filter(\n    (x) =>\n      (x.longitude < 30) &\n      (x.longitude > 10) &\n      (x.latitude > 50) &\n      (x.latitude < 62) &\n      (x.altitude > 5000)\n  )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":53,"value":"import {Plot} from \"@fil/plot-carto-0-5\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"d3 = require(\"d3@7\", \"d3-hexbin@0.2\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"pq = import(\"https://unpkg.com/parquet-wasm@0.1.1/web.js\").then(\n  async (d) => (await d.default(), d)\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"hexagon = {\n  const hex = Array.from({ length: 6 }, (_, i) => [\n    Math.sin((i * Math.PI) / 3),\n    Math.cos((i * Math.PI) / 3)\n  ]);\n  return {\n    draw(context, size) {\n      const s = Math.sqrt(size / Math.PI);\n      for (let i = 0; i < 6; i++)\n        context[i ? \"lineTo\" : \"moveTo\"](hex[i][0] * s, hex[i][1] * s);\n      context.closePath();\n    }\n  };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"countries = d3.json(\n  \"https://unpkg.com/visionscarto-world-atlas@0.0.6/world/50m_countries.geojson\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":501,"value":"*Debug view: the raw data*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":167,"value":"Plot.carto({\n  width,\n  height,\n  projection,\n  marks: [\n    Plot.features(countries.features, {\n      title: (d) => d.properties.sovereignt,\n      stroke: \"black\"\n    }),\n    Plot.feature(d3.geoGraticule10()),\n    Plot.points(data.sample(aq.frac(0.02)), {\n      lonLat: (d) => [d.longitude, d.latitude],\n      r: 0.8,\n      //      fillOpacity: 0.5,\n      //fill: \"HPL\",\n      title: \"callsign\"\n    })\n  ]\n  //color: { scheme: \"reds\", legend: true, percent: true, label: \"HPL > 200 (%)\" }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}}
30:"$2f:body"