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My ADS-B tracker project

Some years ago, I bumped into an article on Mashable about Jeremy Merrill using a Raspberry Pi ADS-B tracker to detect aircraft flying over his house and display the origin or destination of that plane (see article here and github there). As my place is just on a busy plane corridor, that gave me an idea. I decided to work on a similar project based on Piaware. Looking at how he did it and at the long literature you can find on the web on ADS-B, I created this site, my own software in Python to run on my Pi and other fun stuffs. I also ran into this site by SonicGoose and that gave me many new ideas (including the basic structure of this site – I never had any experience of html or php before).

One key part is getting access to aircraft databases to get more info from the ModeS hex code you get from the Piaware tracker. I am sharing my own database of planes, airports and routes I detected with one of my trackers (I have a fixed one at home, another one in Briancon in France (solar powered and connected by SigFox!) and a mobile one I take with me during my trips over the world).

When I started few years ago, I didn’t know that it will become such a fun project!

Updates

[2019/02] Update of installation script and new links
[2019/05] Update of the Radar page that now use my own positions database. Added aircraft silhouettes and Airlines logo.
[2019/05] Changed the domain to FoxtrotCharlie.ovh !!!
[2019/06] Changed landing page and reworked index for Google
[2019/07] Added Great Circle tracks between origin, destination and seen positions on Radar
[2019/09] Added Airports data, API page, better sitemap for Google index
[2020/01] Added a solar powered ADS-B tracker in Briancon, with a SigFox interface by SNOC to send new / special planes to this database when Wifi is off – works great!
Running an ADS-B tracker on a solar panel is quite challenging. After some research, I believed a 20W solar panel would be enough, but the stick consumption is very high, and solar energy production is far from stable… after few month using it, I would need about 80W to be able to power the system for 24h (Raspberry Pi 4 + Flightaware Pro Stick Plus + SNOC SigFox). SigFox is a great solution to replace a 4G modem which would also take too much energy. The limitation to 6 messages per hour is manageable, as I am only reporting new or special planes to this website, while the detailed data are stored and shared when the device has access to wifi. The biggest issue I didn’t plan for was that the Pi doesn’t have a RTC, so time was wrong (it only progress when the Pi is on, about 8 to 12h per day… after few days, it was completely off). Hopefully, I could also use the downlink SigFox messages to get the network time and update the Pi time at each boot. Here the limitation is at 4 messages per day. It is controlled by the callback feature so it is quite easy to be sure you will not exceed the budget, even with a Pi with no idea what is current date or time. Next step is to work on shuting down properly the Pi when battery is low in order to avoid memory issue. So far it works with multiple wild shutdowns per day, but I don’t know for how long.
[2020/02] Updated the stats page to show more details
[2020/03] Added tweets on Sigfox interface with Briancon tracker
[2020/07] Working on adding MoPi-2 on the solar powered tracker to allow clean power down. Changed all the time in UTC. With trackers everywhere, it doesn’t make sens anymore to be on Hong Kong time.
[2020/09] Added a new blog. Let’s hope I will post regularly from now on![2020/10] API optimisation – reduced the errors from 2% to 0.05%
[2020/11] New landing page with a RSS feed reader to get up to date links to my blog posts. Let’s see the impact on Search ranking!

Interesting links

The Mashable article that started everything.
Flyover github, a great place to start.
Piaware from Flightaware.
Raspberry Pi
SonicGoose, that inspired me to create my own database of aircraft, flights, airports…
ADSB-Exchange which has great APIs
The very good adsb-receiver on github
The awesome OpenSky, with it’s great interface
The excellent AboveTustin, if you want to tweet the planes flying over
And for sure Foxtrotcharlie!

US NAVY using ADS-B code hopping

Recently, I started to detect many P8 Poseidon aircraft above South China Sea, like if a dozen of different P8 were flying in the area each day. The only explanation I see is that they are doing ADS-B code hopping, switching to a new TACTICAL code every few minutes.

Here are some of the codes I detected in the past few days: AE686A, AE6879, AE6889, AE67B3, AE6784, AE687D, AE6850, AE6854, AE6809, AE6793, AE6807, AE6845, AE6819, AE6836, AE67C2, AE67DC, AE6885, AE67D6, AE6813, AE687E, AE689E, AE6884, AE67DE, AE6803, AE682D, AE687C, AE6849, AE68A2.

Few more codes detected recently: AE6848, AE67DF, AE6870, AE6883, AE683D, AE6822, AE6814

3 tips to optimize PHP code

How I divided my server errors by 40 with PHP code optimization

I have been running several Raspberry Pi based trackers for a while, and I wanted to create a common database of detected aircraft and their positions. I looked for online database solution and how I could connect my Pi to them directly in Python, but that was not convenient.

I finally decided to get an hosting plan at OVH and create my own databases, with API to add more aircraft and positions. I wrote all the APIs of my server in PHP, as it was pretty straightforward. I got it work pretty well, but I was still having quite a lot of errors. At first, it was simple, I played a little with the timeout, I add retries, but I was still not able to go below 2% of errors. For a long time I lived with that, my system still worked well, but I finally decided to work on that and optimize PHP code.

The usual PHP tips to optimize PHP code…

A quick search on php optimization got me a list of things to do:

  • use single quote instead of double one: 'text' is better than "text"
  • calculate variable only once in a loop
  • close databases
  • order switch by order of use
  • select specific columns instead of * in mySQL SELECT queries
  • use foreach instead of while
  • use echo $a,$b,$c instead of echo $a.$b.$c
  • use sprintf to add strings: $string = sprintf('today is %s', $date)
  • use === instead of == in if: if ($a===$b) { action}
  • INSERT multiple values in database instead of multiple single INSERT

It seems that many of them were useful for older PHP versions, but not really for PHP versions over 7…

… and what really worked for me!

The 3 actions that had a tremendous effect on my API have been around database optimisation: first, I rewrote the few INSERT loops in order to INSERT multiple values at once. This was already much better. Then I checked my databases structures, to make sure I had all the right indexes corresponding to my SELECT queries. And finally, I switched all the heavy ones to InnoDB (I am not sure why OVH use MyISAM as default structure…).

These 3 actions reduced my error rate from 2% to 0.05% by reducing the load of my server (I am using a very basic hosted configuration, nothing fancy here). On the other tips I found, most of them had no or only very marginal impact. The only one I will keep, is the sprintf function to create my strings with variables as this makes my code much easier to read (it was easy to get lost in the quotes when you write mySQL queries with all that ‘ and ” and .).

How did I find that was my issues? What is important is to find where you PHP requests are spending time. For that, I simply implemented some time measurement inside the code (with the microtime function: $start_time=microtime(True); $stop_time=microtime(True); phpduration = $stop_time-$start_time;), that is coming back to my Pi with the result of the API. I could then dig into the one loading the server for more than 1s and reduced their load. I did the same in my Pi, to track which mySQL queries were taking more than 0.001s to run, and that was very efficient.

I was able to focus on optimising the most important ones (mainly those on huge database, such as positions, which rapidly contain millions of entries), and optimise their structure and indexes. There are many tools available to profile your PHP code, but I didn’t find any that was easy enough to start with compared to what I needed them for.

With 0.05% error rate, I can think about adding more trackers and maybe even have a way for others to share their tracking data with me! Let me know if you would share yours or if you have more tips to optimise PHP code…

SigFox for Raspberry Pi

The hardware

First you need to find a Sigfox hat for your Raspberry Pi. Just Google “Sigfox for Raspberry Pi” and you will find the latest solution available. I am using a RPISIGFOX, made my SNOC. Pretty easy to setup and use. Just plug it in, change the serial port parameters, and it is ready to work. It comes with 1 year SigFox subscription that requires activation on Sigfox website. Depending on where you intend to use your Pi, you may need a different version of Sigfox radio (that one is mainly for Europe – US and Asia have different frequency bands for non regulated spectrum).


The Software

  1. Disable Raspberry Pi terminal on serial port with raspi-config utility: sudo raspi-config. Go to Interfacing Options then choose Serial then NO and OK
  2. Install pyserial: sudo apt-get install python-serial
  3. Download scripts: git clone https://github.com/SNOC/rpisigfox.git
  4. Enable script execution: chmod +x sendsigfox.py
  5. Plug antenna with its cable and send your first message: ./sendsigfox.py 0123

Setting up the Callbacks and your server

You also need to setup the callbacks on Sigfox system, and your server to manage the data. This is pretty straightforward with the documentation for the uplink messages. You are limited to 6 uplink messages per hour. On reception of the uplink message, the server will call your API, as you have defined in Sigfox interface. What you do with the data on your server is up to you!

Downlink messages are a little more complex to manage. You are limited to 4 downlink messages per day, and it was not very easy to make sure my Rasberry Pi application was remaining inside this budget, specially with a solar powered Pi and without a RTC … It took me some time to understand that the server was in fact the one making sure you stay in the budget, as if there is no downlink message to send, it won’t count into the 4 messages per day.

To request a downlink message, you just need to send ack=true with your uplink message.

On reception of the uplink request through the above API, your server will have to provide the answer: "[device ID]":{"downlinkData":"[data]"} if there is a downlink payload or "[device ID]":{"noData":true} when there is no payload to send. In that case, the downlink message will not count in your daily budget.

Keeping the Pi on time

As my Raspberry Pi is solar powered (with a 20W solar panel, which is enough for the Pi, but not for the RTL-SDR dongle that has a much bigger power consumption), I don’t necessarily have enough power to keep the Pi on 24/24. When it is off, the time stops to progress, as the Pi doesn’t have a RTC by default. After few days, time and date are completely wrong. That makes it difficult to control the downlink messages budget from the Pi. At the same time, SigFox is a great solution to get the network time to and update the time of the Pi. With the downlink messages, I was able to get the network time when the Pi is starting and update the date and time of the Pi with the simple command sudo date --set="9 JUN 2017 19:15:00".

How I use it?

With the payload limitations at 6 uplink messages per hour (12 bytes) and 4 downlink messages per day (8 bytes), Sigfox doesn’t really replace a Wifi connection, I cannot report all the detected aircrafts and their positions as I am normally doing. As, this is for an ADS-B tracker, I decided to focus on new aircraft and special ones (such as military) for the uplink direction, transmitting only the ModeS hex code and the timestamp at which it was detected, the remaining 4 bytes are used for maintenance purpose (HHHHHHYYYYMMDDHHMMSSXXXX).

To avoid going over 6 uplink messages per hour, each detection will go into a buffer, that is checked every 10 minutes. I have been working on some more compressed way to encode these data but practically I don’t need it, as I am very seldom over budget (meaning I am sending a message every 10 minutes as long as my Pi is powered by the battery). We will see if this is still the case after COVID-19 and the airlines start to have a more international flights. Each time my server receive an uplink message it will automatically generate a tweet (with the #Sigfox hashtag).

Downlink messages are used only to keep the time of the Pi in sync, as described before. As sometimes the Pi doesn’t receive the downlink message or is switched off again when battery is low and weather is grey, it may need more than one downlink per day for time sync. In addition of the network timestamp, I still have 2 bytes available to send other data to the Pi. I am using this for maintenance purpose (YYYYMMDDHHMMSSXX). Note that the uplink message must be exactly 8 bytes in size or it will not go through.

It has been a long time I wanted to play with a Sigfox hat, and it has been quite fun: not that difficult to make it work, but enough issues to solve to make that interesting!

Breitling Jet Team

Breitling Jet Team, operated by Apache Aviation is based in Dijon, a city in France few hundreds kilometres south east of Paris. My mobile tracker picked most of the team when I spent few weeks in Chalon our Saone early this year.

Breitling Jet Team is flying on Aero L39C Albatros, with tails ES-YLX, ES-YLN, ES-YLF, ES-YLP, ES-YLR, ES-TLF, ES-TLG and ES-YLI. You can see more details in the search page.

Breitling has decided in 2019 not to renew its sponsorship as sole and exclusive partner of Apache Aviation, but is open to staying on board as co-sponsor. Apache Aviation and Breitling are in search of co-sponsors to operate Jet Team around the globe.

Founded by Jacques Bothelin in 1980, the team had several sponsors (and names) during the years: Patrouille Martini, Patrouille Ecco, Patrouille Addecco, Khalifa Jet Team before to be named Breitling Jet Team in 2003.

Let’s hope they will find a new partner to continue this adventure!

US military planes in South China Sea

There are a lot of US military activity in the area between Taiwan, Hong Kong and the South China Sea. Transports, SIGINT, reconnaissance, protection of US carriers in the area… mainly conducted by the US Air Force and the US Navy. Here is a list of planes seen in past few months (click on the link to see the radar map when the trackers got a MLAT position – these aircraft generally do not broadcast their position on ADSB):

AE049B – Tail number: 61-0313 – Boeing KC-135R – US Air Force

AE1492 – Tail number: 96-0042 – Boeing E-8C Joint Stars – US Air Force

AE1D8A – Tail number: 15-6511 – Lockheed EP-3E Aries 2 Orion – US Navy

AE1D95- Tail number: 15-9893 – Lockheed EP-3E Orion – US Navy

AE1D91- Tail number: 15-7318 – Lockheed EP-3E Aries2 Orion – US Navy

AE1D5D – Tail number: 16-1586 – Lockheed P-3C-II.2 Orion – US Navy

AE17EF- Tail number: 05-0730 – Boeing C-40C – US Air Force

AE04FD – Tail number: 58-0095 – Boeing KC135T – US Air Force

AE01CE – Tail number: 62-4134 – Boeing RC135W Stratotanker SIGINT – US Air Force

You also can see the latest detected military and other aircraft of interest and the pick of the day or search my database on foxtrotcharlie.ovh.

SAM727 flying over Guangzhou with Secretary Pompeo

Today (2020-10-30), the Boeing C-32A with tail 99-0003 was spotted by my trackers over Guangzhou with the CallSign SAM727.

A quick search shows a departure from Hanoi, and a current position over Japan. Probably used by Secretary Pompeo who was visiting Hanoi yesterday.

Will airlines recover from COVID-19 crisis?

I have been tracking planes in Hong Kong for few years now with my Raspberry Pi based ADSB trackers. There are few airports in range (Hong Kong, Macau, Guangzhou, Shenzhen, Zhuhai, Huizhou), which was giving me quite some traffic (about 2000-2200 different aircraft per day).

Then came COVID-19. Many international airlines stopped to come to China. Many domestic flights were cancelled too. And then the crisis went worldwide. Daily traffic dropped to 600 aircrafts per day at the peak of the crisis.

Since then, it has been slowly recovering. As China domestic traffic went back almost to normal, I am now at 1300-1400 aircraft per day, still far away from where it was.

Bad news are coming from everywhere… Cathay Pacific just announced they will suppress 6000 positions and stop Cathay Dragon. Many smaller airlines have been bankrupt. Most of the others have retired their old or not efficient aircraft earlier than initially planned (B747 and A380 are the most iconic ones).

And restrictions to international travels are still in place in many countries, while the epidemic is restarting in Europe, and never really slow down in US. Can the industry recover from such an unprecedented crisis? I wish it will! My bet is that it will take time and that it will have deeply modified the industry. 2020 will be a turning point in any case and resilience now has to be in every airline strategy.

Sharing my database of Aircraft, Airports and Routes

I have been gathering data for few years now, from multiple sources (databases found online, some special aircraft found manually online, …). I now have more than 32,500 entries in my Aircraft database, including 6,000 that I flagged as “special”, meaning military or any other interesting features (helicopters, rare aircrafts …).

I also have more than 16,000 airports and 160,000 routes.

They are all accessible through dedicated API.

Search aircraft by Mode S code or tail number

You can access my database of aircraft through the following API:
https://www.foxtrotcharlie.ovh/API/public/api?ModeS=XXXXXX
where XXXXXX is the ModeS code of the aircraft, on 6 digits in hexadecimal.
https://www.foxtrotcharlie.ovh/API/public/api?Registration=XXXXXX
where XXXXXX is the tail number (or registration) of the aircraft (in some countries, tail numbers have a – like in China B-8638, it should be put here).
The output is in json format (RFC4627).
Working samples of the API:
https://www.foxtrotcharlie.ovh/API/public/api?ModeS=78102f
https://www.foxtrotcharlie.ovh/API/public/api?Registration=B-8638

Returned data:

      {
          "ModeS":            "78102f",
          "ModeSCountry":     "China",
          "Registration":     "B-8638",
          "ICAOTypeCode":     "A321",
          "Type":             "Airbus A321-211",
          "SerialNo":         "---",
          "RegisteredOwners": "China Southern Airlines",
          "OperatorFlagCode": "CSN",
          "FirstSeen":        "2017-03-25 23:58:09",
          "LastSeen":         "2019-09-06 07:25:41"
      }
DesignatorDescriptionFormat
ModeSModeS code in HEX format of the Aircraft6 characters
ModeSCountryCountry of registration of the Aircraftstring
RegistrationTail Number of the Aircraftstring
ICAOTypeCodeICAO Type Code of the Typestring
TypeType of Aircraftstring
SerialNoSerial Number of the Aircraftstring
RegisteredOwnersRegistered Owners of the Aircraftstring
OperatorFlagCodeCode of the Airline if anystring
FirstSeenTime stamp when my trackers first detected the AircraftTimestamp
LastSeenTime stamp when my trackers last detected the AircraftTimestamp
Json structure description for Aircraft API

Search airports by ICAO code

You can also access my database of airports through the following API:
https://www.foxtrotcharlie.ovh/API/public/api?ICAO=XXXX
where XXXX is the ICAO code of the airport on 4 characters.
The output is in json format (RFC4627).
Working samples of the API:
https://www.foxtrotcharlie.ovh/API/public/api?ICAO=VHHH

Returned data:

      {
          "ICAO":       "VHHH",
          "IATA":       "HKG",
          "Name":       "Hong Kong International Airport",
          "Location":   "Hong Kong",
          "Region":     "Hong Kong",
          "Latitude":   22.3089,
          "Longitude":  113.915
       }
DesignatorDescriptionFormat
ICAOICAO code of the Airport4 characters
IATAIATA code of the Airport3 characters
NameName of the Airportstring
LocationLocation of the Airport in clearstring
RegionRegion or Country of the Airportstring
LatitudeLatitude of the Airportfloat
LongitudeLongitude of the Airportfloat
Json structure description for Airport API

Search routes by Flight Number (ICAO format)

You can also access my database of routes through the following API:
https://www.foxtrotcharlie.ovh/API/public/api?FNB=XXXXXX
where XXXXXX is the flight number in ICAO format.
The output is in json format (RFC4627).
Working samples of the API:
https://www.foxtrotcharlie.ovh/API/public/api?FNB=AFR188

Returned data:

      {
          "FNB":            "AFR188",
          "Airline":        "AFR",
          "FlightNumber":   "188",
          "Origin":         "LFPG",
          "Destination":    "VHHH",
          "Via":            ""
       }
DesignatorDescriptionFormat
FNBFlight number in ICAO formatstring
AirlineICAO code of the airline4 characters
FlightNumberFlight numberstring
OriginOrigin airport (ICAO format)string
DestinationDestination airport (ICAO format)string
ViaVia airport – if any (ICAO format)string
Json structure description for Airports API

Disclaimer

All the information provided by these API are provided as is and for information only. They are coming from different sources and may contain mistakes or be out of date. Please use with caution and at your own risk.

You are welcome to comment if you see mistakes. Mode S codes can be re-allocated to new aircraft, and keeping the database up to date is not an easy task.

G-IRTY Spitfire flying over Hong Kong in 2019

One of the most surprising catch of 2019 was for sure seeing a Spitfire in my new aircraft list! I had to check if that was correct or a mistake somewhere in the database of Mode S codes I collected.

It turned out it was the real thing! The Silver Spitfire was doing The Longest Flight, for the 75th anniversary of the D-Day invasion. A 30 legs, 22,138 miles trip around the world.

These guys rock!