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sdr-enthusiasts/docker-adsb-ultrafeeder

• sdr-enthusiasts/docker-adsb-ultrafeeder
  • Introduction
  • Up-and-Running Quickly with docker-compose
  • Ports
  • Runtime Environment Variables
    • General Configuration
      • Basic Ultrafeeder Parameters
        • Mandatory Parameters
        • Optional Parameters
    • Getting ADSB data to the Ultrafeeder
      • Connecting to an SDR or other hardware device
        • Mandatory parameters
        • Optional/Additional Parameters
        • AutoGain for RTLSDR Devices
      • Connecting to external ADSB data sources
        • All-in-One Configuration using ULTRAFEEDER_CONFIG
        • Networking parameters
        • Feeding directly from Ultrafeeder
        • Alternate Configuration Method with READSB_NET_CONNECTOR
      • Optional Networking Parameters
      • MLAT configuration
      • MLAT troubleshooting
      • Configuring the built-in MLAT Hub
    • Web Gui (tar1090) Configuration
      • tar1090 Core Configuration
      • tar1090 config.js Configuration - Title
      • tar1090 config.js Configuration - Output
      • tar1090 config.js Configuration - Map Settings
      • tar1090 config.js Configuration - Range Rings
      • tar1090 config.js Configuration - Expert
      • tar1090 config.js Configuration - Route Display
    • graphs1090 Configuration
      • graphs1090 Environment Parameters
      • Enabling UAT data
      • Enabling AirSpy graphs
      • Enabling Disk IO and IOPS data
      • Configuring the Core Temperature graphs
      • Reducing Disk IO for Graphs1090
    • timelapse1090 Configuration
  • Updating your location with GPSD
    • Basic Installation and Configuration of your GPS hardware and gpsd drivers
    • Optional parameters regulating the restart of mlat-client when the location changes
  • Web Pages
  • Paths
  • Display of Metrix with Grafana and Prometheus/InfluxDB
    • Configuring Grafana
    • Output from Ultrafeeder to Prometheus
    • Output from Ultrafeeder to InfluxDBv2
  • Message decoding introspection
  • Minimalist setup
  • Logging
  • Getting help
  • License and Trademarks
    • GPLv3 License
    • Trademarks
  • Acknowledgements

Introduction

adsb-ultrafeeder™ is an ADS-B data collector container that can be used to:

• retrieve ADS-B data from your SDR or other device
• display it on a local map, including options to show tracks, heatmaps, and system performance graphs
• forward the data to one or more aggregators using BEAST/BEAST-REDUCE/BEAST-REDUCE-PLUS format
• send MLAT data to these aggregators
• receive and consolidate MLAT results data (built-in mlathub)
• Interface with external visualization tools such as Grafana using statistics data available in InfluxDB and Prometheus format

In order to accomplish this, the container makes use of the following underlying technologies:

• SDR-Enthusiasts™ Docker Base-Image
• Wiedehopf's branch of readsb
• Wiedehopf's tar1090 graphical interface
• Wiedehopf's graphs1090
• MLAT Client

It builds and runs on linux/amd64, linux/arm/v7 (linux/armhf) and linux/arm64 architectures.

Up-and-Running Quickly with docker-compose

• An example docker-compose.yml file can be found in this repository.
• The accompanying environment variable values are defined in the .env file in this repository

Once you have installed Docker, you can follow these lines of code to get up and running in very little time:

sudo mkdir -p -m 777 /opt/adsb
cd /opt/adsb
wget https://raw.githubusercontent.com/sdr-enthusiasts/docker-adsb-ultrafeeder/main/docker-compose.yml
wget https://raw.githubusercontent.com/sdr-enthusiasts/docker-adsb-ultrafeeder/main/.env

Then edit the docker-compose.yml and .env files and make any changes as needed. Please configure ALL variables in .env:

nano docker-compose.yml
nano .env

Finally, bring up the stack. This may take a minute as it will automatically download the container and start it up:

docker compose up -d

Ports

Some common ports are as follows (which may or may not be in use depending on your configuration). You can override the port mappings with the parameters shown in the Optional Networking Parameters section.

The general principle behind the port numbering, is:

• 30xxx ports are connected to the main instance readsb that decodes and processes the SDR data
• 31xxx ports are connected to the MLAT Hub
• 92xx ports are for Prometheus statistics output
• 80 contains the Tar1090 web interface

Any of these ports can be made available to the host system by using the ports: directive in your docker-compose.yml. The container's web interface is rendered to port 80 in the container. This can be mapped to a port on the host using the docker-compose ports directive. In the example docker-compose.yml file, the container's Tar1090 interface is mapped to 8080 on the host system, and ports 9273-9274 are exposed as-is:

    ports:
      - 8080:80               # to expose the web interface
      - 9273-9274:9273-9274   # to expose the statistics interface to Prometheus

Json position output:

• outputs an aircraft object for every new position received for an aircraft. The following parameters (which can be added with READSB_EXTRA_ARGS) control this output:
• --net-json-port-interval Set minimum interval between outputs per aircraft for TCP json output, default: 0.0 (every position)
• --net-json-port-include-noposition TCP json position output: include aircraft without position (state is sent for aircraft for every DF11 with CRC if the aircraft hasn't sent a position in the last 10 seconds and interval allowing)
• each json object will be on a new line
• https://github.com/wiedehopf/readsb/blob/dev/README-json.md

Aircraft.json:

• https://github.com/wiedehopf/readsb/blob/dev/README-json.md
• available on the same port as the web interface, example: http://192.168.x.yy:8087/data/aircraft.json

Runtime Environment Variables

The sections below describe how to configure each part of the container functionality. Each section describes what's needed to come up with a minimally viable configuration, followed by additional / optional parameters that can also be set.

Note:

• to enable a parameter, you can set it to any of 1, true, on, enabled, enable, yes, or y. In the table below, we'll simply use true for convenience.
• to disable a parameter, you can set it to anything else or simply leave it undefined.

General Configuration

You need to make sure that the USB device can be accessed by the container. The best way to do so, is by adding the following to your docker-compose.yml file:

    device_cgroup_rules:
      - 'c 189:* rwm'
...
    volumes:
      - /dev:/dev:rw

The advantage of doing this (over simply adding a device: directive pointing at the USB port) is that the construction above will automatically recover if you "hot plug" your dongle. ⚠️This feature requires a recent version of docker-compose (version >=2.3). Make sure your system is up to date if dongles are not found. ⚠️

Basic Ultrafeeder Parameters

Mandatory Parameters

The following parameters must be set (mandatory) for the container to function:

Optional Parameters

READSB_EXTRA_ARGS just passes arguments to the commandline, you can check this file for more options for wiedehopf's readsb fork: https://github.com/wiedehopf/readsb/blob/dev/help.h

Getting ADSB data to the Ultrafeeder

There are two ways to provide ADSB data to the Ultrafeeder:

• provide the container with access to an SDR or other hardware device that collects ADSB data
• allow the container to connect to a ADSB data source in Beast, Raw, or SBS format

These methods are not mutually exclusive - you can use both at the same time if you want.

Connecting to an SDR or other hardware device

If you want to connect your SDR to the container, here's how to do that:

Mandatory parameters

Optional/Additional Parameters

AutoGain for RTLSDR Devices

If you have set READSB_GAIN=autogain, then the system will take signal strength measurements to determine the optimal gain. The AutoGain functionality is based on a (slightly) modified version of Wiedehopf's AutoGain. AutoGain will only work with rtlsdr style receivers.

Note that AutoGain is not related to the SDR's AGC setting (controlled with the READSB_RTLSDR_ENABLE_AGC variable). We do not recommend enabling AGC for Ultrafeeder or any other ADS-B decoder.

There are 2 distinct periods in which the container will attempt to figure out the gain:

• The initial period of 2 hours, in which an adjustment is done every 5 minutes
• The subsequent period, in which an adjustment is done once every day

Please note that in order for the initial period to complete, the container must run for 90 minutes without restarting.

When taking measurements, if the percentage of "strong signals" (i.e., ADSB messages with RSSI > 3 dB) is larger than 6%, AutoGain will reduce the receiver's gain by 1 setting. Similarly, if the percentage of strong signals is smaller than 2.5%, AutoGain will increment the receiver's gain by 1 setting. When AutoGain changes the gain value, the readsb component of the container will restart. This may show as a disconnect / reconnected in container logs.

We recommend running the initial period during times when there are a lot of planes overhead, so the system will get a good initial view of what signals look like when traffic is at its peak for your location. If you forgot to do this for any reason, feel free to give the AutoGain reset command (see below) during flights busy hour.

Although not recommended, you can change the measurement intervals and low/high cutoffs with these parameters:

If you need to reset AutoGain and start over determining the gain, you can do so with this command:

docker exec -it ultrafeeder /usr/local/bin/autogain1090 reset

Connecting to external ADSB data sources

In addition to (or instead of) connecting to an SDR or hardware device to get ADSB data, the container also supports ingesting or sending data from a TCP port. Here are some parameters that you need to configure if you want to make this happen:

All-in-One Configuration using ULTRAFEEDER_CONFIG

ULTRAFEEDER_CONFIG is a new parameter that can be used instead of separately defining READSB_NET_CONNECTOR, MLAT_NET_CONNECTOR, MLATHUB_NET_CONNECTOR/MLATHUB_CONFIG. These legacy parameters will still work; however, we wanted to provide a single parameter that enables configuration of incoming and outgoing ADSB data, MLAT-client data, and MLATHUB data.

Note that ULTRAFEEDER_CONFIG and ULTRAFEEDER_NET_CONNECTOR can be used interchangeably; in this documentation, we'll use ULTRAFEEDER_CONFIG as an example.

ULTRAFEEDER_CONFIG syntax:

The ULTRAFEEDER_CONFIG parameter can have multiple config strings, separated by a ;. Please note that the config strings cannot contain ; or , -- undefined things may happen if these characters are present.

- ULTRAFEEDER_CONFIG=adsb,host,port,protocol[,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,extra-arguments]
...or...
- ULTRAFEEDER_CONFIG=mlat,host,port[,return_port][,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,extra-arguments]
...or to retrieve MLAT data from a remote receiver...
- ULTRAFEEDER_CONFIG=mlat,host,port[,return_port][,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,input_connect=remote-host:port,lat=xx.xxxx,lon=yy.yyyy,alt=zzz][,extra-arguments]
...or...
- ULTRAFEEDER_CONFIG=mlathub,host,port,protocol[,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,extra-arguments]

• To connect to an external ADSB (for input or output), UAT, or MLAT results source, use - ULTRAFEEDER_CONFIG=adsb,host,port,protocol[,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,extra-arguments]
• To connect and send data to an MLAT Server, use - ULTRAFEEDER_CONFIG=mlat,host,port[,return_port][,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,name=Friendly_Name-123][,input_connect=remote-host:port,lat=xx.xxxx,lon=yy.yyyy,alt=zzz][,extra-arguments]. For the optional parts in this structure, see MLAT configuration. Note - any MLAT results data received from the MLAT Server will automatically be aggregated in an MLAT Hub and shared with tar1090
• To add MLAT results from additional MLAT Servers not configured with Ultrafeeder (for example, MLAT results from FlightRadar24 or FlightAware/piaware), use - ULTRAFEEDER_CONFIG=mlathub,host,port,protocol[,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX][,extra-arguments]. You can further configure this MLAT Hub as described in the section Configuring the built-in MLAT Hub

In the above configuration strings:

• host is an IP address. Specify an IP/hostname/containername for incoming or outgoing connections.
• port and return_port are TCP port numbers
• protocol can be one of the following:
  • beast_reduce_out: Beast-format output with lower data throughput (saves bandwidth and CPU)
  • beast_reduce_plus_out: Beast-format output with extra data (UUID). This is the preferred format when feeding the "new" aggregator services
  • beast_out: Beast-format output
  • beast_in: Beast-format input
  • raw_out: Raw output
  • raw_in: Raw input
  • sbs_out: SBS-format output
  • vrs_out: SBS-format output
  • uat_in: "special" RAW format input as generated by the dump978 container on port 30978. It is advisable to use this protocol and port to get UAT data from dump978, for example: - ULTRAFEEDER_CONFIG=adsb,dump978,30978,uat_in
• uuid is a Universally Unique Identifier. You can reuse the one you generated for AdsbExchange, or you can generate a new one with this Linux command: cat /proc/sys/kernel/random/uuid. If omitted, it will use the UUID environment parameter, or if that one doesn't exist, it will leave the field empty.
• name is a friendly name (containing any character of the set [A-Za-z0-9_-] - do not use any spaces, quotes, or other non-alphanumeric characters!) that will be sent to the MLAT Server, used to identify the station by name. If omitted, it will use the MLAT_USER parameter, or if that one doesn't exist, it will leave the field empty.

Networking parameters

Feeding directly from Ultrafeeder

There are several aggregators, both non-profit and commercial, that can directly be sent data from ultrafeeder without the need for an additional feeder container. We have added them in the example docker-compose.yml snippet above. Here is a partial list of these aggregators. All of them use the beast_reduce_plus format for feeding ADSB data, and mlat-client for feeding MLAT:

When feeding AdsbExchange, Ultrafeeder will send statistics to adsbexchange.com by default. See the description of the ADSBX_STATS parameter on how to disable this.

To feed AussieADSB (Australia/Oceania only!), execute this command on your host and follow the instructions. You can also use this command to de-register your feeder, or to see its status:

bash <(wget -qO - https://raw.githubusercontent.com/sdr-enthusiasts/docker-adsb-ultrafeeder/dev/aussieadsb.sh)

Alternate Configuration Method with READSB_NET_CONNECTOR

Instead of (or in addition to) using BEASTHOST, you can also define ADSB data ingests using the READSB_NET_CONNECTOR parameter. This is the preferred way if you have multiple sources or destinations for your ADSB data. This variable allows you to configure incoming and outgoing connections. The variable takes a semicolon (;) separated list of host,port,protocol[,uuid=XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX], see the section All-in-One Configuration using ULTRAFEEDER_CONFIG for explanation of these parameters.

NOTE: If you have a UAT dongle and use dump978 to decode this, you should use READSB_NET_CONNECTOR to ingest UAT data from dump978. See example below

    environment:
    ...
      - READSB_NET_CONNECTOR=dump978,30978,uat_in;...
    ...

Optional Networking Parameters

There are many optional parameters relating to the ingestion of data and the general networking functioning of the readsb program that implements this functionality.

MLAT configuration

The Ultrafeeder contains a capability to send MLAT data to MLAT servers to be processed, and to receive the MLAT results and integrate those with an MLAT Hub and the tar1090 map. It will create a separate instance of mlat-client for each defined MLAT server. The parameters for these mlat-client instances is as follows:

    environment:
    ...
      - ULTRAFEEDERCONFIG=
           ...
           mlat,mlat-server1.com,port1,return_port1,uuid=1234-5678-90123,inputconnect=remote_receiver1:30005,lat=12.3456,lon=45.6789,alt=18m,--arg1 hello --arg2 world;
           mlat,mlat-server2.com,port2,return_port2,uuid=5678-9012-34567,inputconnect=remote_receiver2:30005,-lat=12.3456,lon=45.6789,alt=18m,--arg1 hello-again --arg2 universe
    ...
      - MLAT_USER=some_friendly_user_name_using_only_alphanumeric_characters_without_spaces_or_quotes

where:

Note - the optional parameters can be given in any order.

The MLAT_USER parameter is passed to the MLAT Client and server, and will show up as a "friendly" name on MLAT related stats at your MLAT aggregator. This parameter can only contain alphanumeric (a-z, A-Z, 0-9) characters, dashes (-), or underscores (_).

MLAT troubleshooting

Sometimes, MLAT appears not to be working correctly and you will see messages with high bad_sync_timeout values, like this:

[2024-06-29 11:31:20.385][mlat-client][in.adsb.lol] peer_count:  15 outlier_percent: 4.6 bad_sync_timeout: 870

Here are a few things you may want to try to fix this:

• Ensure your longitude, latitude, and altitude are ACCURATE

• Make sure your device's clock is synced continuously with a reliable NTP service. We recommend chronyd over systemd.timesyncd

• Do not try to send MLAT data from a centralized instance when you are using a remote receiver. Instead, feed MLAT directly from the remote station

• On Raspberry Pi 3/3B+, disable HealthCheck by adding the following to the ultrafeeder service section in your docker-compose.yml file. (This has to do with docker resource spikes that mess with MLAT timing on slower machines like the Pi3/3B+) :

    ultrafeeder:
    ...
      healthcheck:
        disable: true
  

• MLAT often fails when you run your receiver on a Virtual Machine rather than directly on the hardware. Avoid virtual machines (including ProxMox and container-in-container setups) or disable MLAT on them

• For FlightAware MLAT, make sure that your location and altitude are PRECISELY defined in your dashboard on the FlightAware website

• Never, ever, ever resend MLAT results back to ADSB or MLAT aggregators. Please DO NOT. This will ensure your data is discarded and may get you banned from the aggregator

• If you feed your data to multiple aggregators, please do not enable MLAT for FlightRadar24 (per their request). Note that MLAT for FR24 using our containerized setup is disabled by default

Configuring the built-in MLAT Hub

An "MLAT Hub" is an aggregator of MLAT results from several sources. Since the container is capable of sending MLAT data to multiple ADSB aggregators (like adsb.lol/fi/one, etc), we built in a capability to:

• collect the MLAT results from all of these services
• ingest MLAT results from other containers (FlightAware, Radarbox, etc.)
• make the consolidated MLAT results available on a port in Beast or SBS (BaseStation) format
• create outbound connections using any supported format to send your Beast data wherever you want

Note - due to design limitations of readsb, the tar1090 graphical interface will by default ONLY show MLAT results from the aggregators/MLAT sources that were defined with the MLAT_NET_CONNECTOR or ULTRAFEEDER_CONFIG=mlat,... parameters. If you want to show any MLAT results from sources that have their own feeder containers (for example, those from piaware), you should add these sources like this:

   - ULTRAFEEDER_CONFIG=mlathub,host,port,protocol;

Where:

• host is the hostname where the MLAT results are coming from. This can be another container name (e.g., piaware) or the IP address of your machine on which mlat-client is running. Note -- this is NOT the hostname or IP of the MLAT Server or aggregator that processes the MLAT data
• port is the port on which the mlat-client on the host makes its results available
• protocol is the output protocol which is almost always beast_in

For example:

   - ULTRAFEEDER_CONFIG=mlathub,piaware,30105,beast_in;

Generally, there is little else to configure, but there are a few parameters that you can set or change:

Web Gui (tar1090) Configuration

The Container creates an interactive web interface displaying the aircraft, based on Wiedehopf's widely used tar1090 software.

The web interface is rendered to port 80 in the container. This can be mapped to a port on the host using the docker-compose ports directive.

All of the variables below are optional.

Note - due to design limitations of readsb, the tar1090 graphical interface will by default ONLY show MLAT results from the aggregators/MLAT sources that were defined with the MLAT_NET_CONNECTOR parameter. If you want to show any additional MLAT results (for example, those from piaware), you should add a separate READSB_NET_CONNECTOR entry for them.

tar1090 Core Configuration

• For documentation on the aircraft.json format see this page: https://github.com/wiedehopf/readsb/blob/dev/README-json.md
• TAR1090_ENABLE_AC_DB causes readsb to load the tar1090 database as a csv file from this repository: https://github.com/wiedehopf/tar1090-db/tree/csv

tar1090 config.js Configuration - Title

tar1090 config.js Configuration - Output

tar1090 config.js Configuration - Map Settings

tar1090 config.js Configuration - Range Rings

tar1090 config.js Configuration - Expert

• In case a setting is available in tar1090 but not exposed via environment variable for this container
• For a list of possible settings, see https://github.com/wiedehopf/tar1090/blob/master/html/config.js
• Incorrect syntax or any capitalization errors will cause the map to not load, you have been warned!
• Example: TAR1090_CONFIGJS_APPEND= MapDim=false; nexradOpacity=0.2;
• In the environment section of a compose file you can generally use multiple lines like this:

    environment:
    ...
      - TAR1090_CONFIGJS_APPEND=
        MapDim=false;
        nexradOpacity=0.2;
    ...

tar1090 config.js Configuration - Route Display

graphs1090 Configuration

graphs1090 Environment Parameters

Enabling UAT data

ADS-B over UAT data is transmitted in the 978 MHz band, and this is used in the USA only. To display the corresponding graphs, you should:

1. Set the following environment parameters:

      - ENABLE_978=yes
      - URL_978=http://dump978/skyaware978

2. Install the docker-dump978 container. Note - only containers downloaded/deployed on/after Feb 8, 2023 will work.

Note that you must configure URL_978 to point at a working skyaware978 website with aircraft.json data feed. This means that the URL http://dump978/skyaware978/data/aircraft.json must return valid JSON data to this tar1090 container.

Enabling AirSpy graphs

Users of AirSpy devices can enable extra graphs1090 graphs by configuring the following:

1. Set the following environment parameters:

      - ENABLE_AIRSPY=yes
      - URL_AIRSPY=http://airspy_adsb

2. Install the airspy_adsb container. Note - only containers downloaded/deployed on/after May 9th, 2024 will work with this method.

Enabling Disk IO and IOPS data

To allow the container access to the Disk IO data, you should map the following volume:

    volumes:
      - /proc/diskstats:/proc/diskstats:ro
      ...

Configuring the Core Temperature graphs

By default, the system will use the temperature available at Thermal Zone 0. This generally works well on Raspberry Pi devices, and no additional changes are needed.

On different devices, the Core Temperature is mapped to a different Thermal Zone. To ensure the Core Temperature graph works, follow these steps

First check out which Thermal Zone contains the temperature you want to monitor. On your host system, do this:

for i in /sys/class/thermal/thermal_zone* ; do echo "$i - $(cat ${i}/type) - $(cat ${i}/temp 2>/dev/null)"; done

Something similar to this will be show:

/sys/class/thermal/thermal_zone0 - acpitz - 25000
/sys/class/thermal/thermal_zone1 - INT3400 Thermal - 20000
/sys/class/thermal/thermal_zone2 - TSKN - 43050
/sys/class/thermal/thermal_zone3 - NGFF - 32050
/sys/class/thermal/thermal_zone4 - TMEM - 39050
/sys/class/thermal/thermal_zone5 - pch_skylake - 40500
/sys/class/thermal/thermal_zone6 - B0D4 - 54050
/sys/class/thermal/thermal_zone7 - iwlwifi_1 -
/sys/class/thermal/thermal_zone8 - x86_pkg_temp - 57000

Repeat this a few times to ensure that the temperature varies and isn't hardcoded to a value. In our case, either Thermal Zone 5 (pch_skylake is the Intel Core name) or Thermal Zone 8 (the temp of the entire SOC package) can be used. Once you have determined which Thermal Zone number you want to use, map it to a volume like this. Make sure that the part to the left of the first : reflects your Thermal Zone directory; the part to the right of the first : should always be /sys/class/thermal/thermal_zone0:ro.

Note that you will have to add - privileged: true capabilities to the container. This is less than ideal as it will give the container access to all of your system devices and processes. Make sure you feel comfortable with this before you do this.

    privileged: true
    volumes:
      - /sys/class/thermal/thermal_zone8:/sys/class/thermal/thermal_zone0:ro
      ...

Note - on some systems (DietPi comes to mind), /sys/class/thermal/ may not be available.

Reducing Disk IO for Graphs1090

Note - this feature is still somewhat experimental. If you are really attached to your statistics/graphs1090 data, please make sure to back up your mapped drives regularly

If you are using a Raspberry Pi or another type of computer with an SD card, you may already be aware that these SD cards have a limited number of write-cycles that will determine their lifespan. In other words - a common reason for SD card failure is excessive writes to it.

By the nature of having to log lots of data the graphs1090 functionality writes a lot to the SD card. To reduce the number of write cycles, there are a few parameters you can set.

Enabling this functionality will cause graphs1090 to temporarily write all data to volatile memory (/run) instead of persistent disk space (/var/lib/collectd). This data is backed up to persistent disk space in regular intervals and upon (graceful) shutdown of the container.

Note -- there is a chance that the data isn't written back in time (due to power failures, non-graceful container shutdowns, etc), in which case you may lose statistics data that has been generated since the last write-back.

The feature assumes that you have mapped /var/lib/collectd to a volume (to ensure data is persistent across container recreations), and /run as a tmpfs RAM disk, as shown below and also as per the docker-compose.yml example:

    volumes:
      - /opt/adsb/ultrafeeder/globe_history:/var/globe_history
...
    tmpfs:
      - /run:exec,size=256M
...

timelapse1090 Configuration

Legacy: We recommend AGAINST enabling this feature as it has been replaced with http://dockerhost:port/?replay. timelapse1090 writes a lot of data to disk, which could shorten the lifespan of your Raspiberry Pi SD card. The replacement functionality is better and doesn't cause any additional disk writes.

Updating your location with GPSD

This feature enables you to deploy Ultrafeeder while you are moving around. It will read your current longitude/latitude/altitude from a GPS unit that is connected to gpsd on your host system, and ensure that the map will show your current location. It will also restart any mlat-client instances once it detects that you moved from your previous location.

Basic Installation and Configuration of your GPS hardware and gpsd drivers

The simplest way of getting this to work is to acquire a "VK163" USB GPS "Mouse", similar to the one in the link. You can connect this mouse to any USB port on your machine.

For this to work, you should install and configure GPSD to work on your host machine. The DEVICES parameter is probably correct as shown below, but you may want to double-check that data is received on that device (cat /dev/ttyACM0) and adjust it if needed:

sudo apt update && sudo apt install -y gpsd
cat << EOM | sudo tee /etc/default/gpsd
# Devices gpsd should collect to at boot time.
# They need to be read/writeable, either by user gpsd or the group dialout.
DEVICES="/dev/ttyACM0"
# Other options you want to pass to gpsd
GPSD_OPTIONS="-G"
# Automatically hot add/remove USB GPS devices via gpsdctl
USBAUTO="true"
EOM
cat << EOM | sudo tee /lib/systemd/system/gpsd.socket
[Unit]
Description=GPS (Global Positioning System) Daemon Sockets

[Socket]
ListenStream=/run/gpsd.sock
ListenStream=[::]:2947
ListenStream=0.0.0.0:2947
SocketMode=0600
BindIPv6Only=yes

[Install]
WantedBy=sockets.target
EOM
sudo systemctl daemon-reload
sudo systemctl restart gpsd gpsd.socket

Then, you can add the following values to ultrafeeder service settings in docker-compose.yml:

services:
...
  ultrafeeder:
    ...
    extra_hosts:
      - "host.docker.internal:host-gateway"
    ...
    environment:
      ULTRAFEEDER-CONFIG=
        gpsd,host.docker.internal,2947;
    ...

Finally, restart the container with docker compose up -d

This will:

• install and configure gpsd (/etc/default/gpsd) so it makes GPS data available on the default TCP port 2947 of your host system
• configure the ultrafeeder docker container to read GPSD data
• configure the ultrafeeder container so the hostname host.docker.internal always resolves to the IP address of the underlying machine (where gpsd is running)

If you have any issues, readsb will use verbose output if you add the GPSD_DEBUG=true as an environment variable.

Optional parameters regulating the restart of mlat-client when the location changes

The following parameters are all optional and are subject to change. These variables should be added to the environment section of your docker-compose.yml. They will not work if entered into the .env file. You don't need to set them unless you want to change the default behavior.

See example below:

    environment:
    ...
      - GPSD_MIN_DISTANCE=20
      - GPSD_MLAT_WAIT=90
      - GPSD_CHECK_INTERVAL=30
    ...

Web Pages

If you have configured the container as described above, you should be able to browse to the following web pages: You should now be able to browse to:

• http://dockerhost/ to access the tar1090 web interface.
• http://dockerhost/?replay to see a replay of past data
• http://dockerhost/?heatmap to see the heatmap for the past 24 hours
• http://dockerhost/?heatmap&realHeat to see a different heatmap for the past 24 hours
• http://dockerhost/?pTracks to see the tracks of all planes for the past 24 hours
• http://dockerhost/graphs1090/ to see performance graphs

Paths

No paths need to be mapped through to persistent storage. However, if you don't want to lose your range outline and aircraft tracks/history and heatmap / replay data on container restart, you can optionally map these paths:

Display of Metrix with Grafana and Prometheus/InfluxDB

When using the :telegraf tag, the image contains Telegraf, which can be used to capture metrics from ultrafeeder if an output is enabled.

See README-grafana.md for detailed instruction on how to configure this.

NOTE - READ CAREFULLY: As of 27 April 2023, the latest image no longer contains Telegraf. If you want to send metrics to InfluxDB or Prometheus, please use this image:

services:
  ultrafeeder:
    image: ghcr.io/sdr-enthusiasts/docker-ultrafeeder:telegraf
  ...

Configuring Grafana

Please see the separate instruction document for step by step instructions on how to set up and configure a Grafana Dashboard with Prometheus. The sections below are provided as a reference.

Output from Ultrafeeder to Prometheus

In order for Telegraf to serve a Prometheus endpoint, the following environment variables can be used:

Output from Ultrafeeder to InfluxDBv2

In order for Telegraf to output metrics to an InfluxDBv2 time-series database, the following environment variables can be used:

Message decoding introspection

You can look at individual messages and what information they contain, either for all or for an individual aircraft by hex:

# only for hex 3D3ED0
docker exec -it ultrafeeder /usr/local/bin/viewadsb --show-only 3D3ED0

# for all aircraft
docker exec -it ultrafeeder /usr/local/bin/viewadsb --no-interactive

# show position / CPR debugging for hex 3D3ED0
docker exec -it ultrafeeder /usr/local/bin/viewadsb --cpr-focus 3D3ED0

Minimalist setup

If you want to use ultrafeeder only as a SDR decoder but without any mapping or stats/graph websites, without MLAT connections or MLAT-hub, etc., for example to minimize CPU and RAM needs on a low CPU/memory single board computer, then do the following:

• in the ULTRAFEEDER_CONFIG parameter, remove any entry that starts with mlat or mlathub. This will prevent any mlat-clients or mlathub instances to be launched. If you still want to connect the mlat-client(s) to external MLAT servers but you don't want to run the overhead of a MLATHUB, you can leave any entries starting with mlat in the ULTRAFEEDER_CONFIG parameter, and set MLATHUB_DISABLE=true
• Set the parameter TAR1090_DISABLE=true. This will prevent the nginx webserver and any websites to be launched and no collectd (graphs1090) or rrd (ADSB message history) data to be collected or retained.
• Make sure to use ghcr.io/sdr-enthusiasts/docker-adsb-ultrafeeder:latest and specifically NOT the ghcr.io/sdr-enthusiasts/docker-adsb-ultrafeeder:telegraf label as Telegraf adds a LOT of resource use to the container

Offline maps

There is the option to use some basic offline maps limited in zoom:

• Download the tiles (don't install tar1090): https://github.com/wiedehopf/adsb-wiki/wiki/offline-map-tiles-tar1090
• Add a volume mapping so the container can access the tiles:

    volumes:
        - /usr/local/share/osm_tiles_offline:/usr/local/share/osm_tiles_offline

Logging

All logs are to the container's stdout and can be viewed with docker logs -t [-f] container.

Getting help

Please feel free to open an issue on the project's GitHub.

We also have a Discord channel, feel free to join and converse.

License and Trademarks

GPLv3 License

Copyright (C) 2023-2024, Ramon F. Kolb kx1t, and other contributors

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

Trademarks

• ultrafeeder, Ultrafeeder, docker-adsb-ultrafeeder are Trademarks owned by Ramon F. Kolb and the SDR-Enthusiasts organization
• SDR-Enthusiasts and SDR-E are a Trademark owned by the SDR-Enthusiasts organization
• Other terms are trademarks of their respective owners

Acknowledgements

• The SDR-Enthusiasts team (Mike Nye, Fred Clausen) for all the foot and leg work done to create the base images on which the container is built
• Wiedehopf for modifying, creating, maintaining, and adding features to many of the components of this container including readsb, tar1090, graphs1090, autogain, and many more components, and for helping debug the container whenever the need arose
• John Norrbin for his ideas, testing, feature requests, more testing, nagging, pushing, prodding, and overall efforts to make this a high quality container and for the USB "hotplug" configuration
• The community at the SDR-Enthusiasts Discord Server for helping out, testing, asking questions, and generally driving to make this a better product
• Of course the Open Source community at large, including Salvatore Sanfilippo and Oliver Jowett who wrote the excellent base code for dump1090 from which much of this package is derived