ganlubbq/orbcomm-receiver

A software decoder for ORBCOMM satellite transmissions.

ORBCOMM receiver

A software receiver for ORBCOMM satellite transmissions.

Please read the wiki for more information: https://github.com/fbieberly/ORBCOMM-receiver/wiki

Description

This is a software receiver for decoding packets from ORBCOMM satellites. For known packet types the packet data is decoded.

I am writing this decoder as an instructional personal project. Hopefully it can be used by others to learn about designing satellite communication receivers.

If you want a more full-featured ORBCOMM receiver please check out:
https://www.coaa.co.uk/orbcommplotter.htm
http://f6cte.free.fr/index_anglais.htm

Dependencies

Should work with either Python 2.X or 3.X

I use:
pyrtlsdr to record the RF signal with an RTLSDR receiver.
NumPy and SciPy are used for signal processing.
PyEphem is used to calculate Az/El and doppler shift of the satellites.
Matplotlib is used for plotting data.

pip install pyrtlsdr, numpy, scipy, pyephem, matplotlib

Getting started

Offline recording and decoding

1. First run the update_orbcomm_tle.py script to get the latest two-line elements for the ORBCOMM satellites.
2. Update latitude and longitude of your receiver in CONFIG.py
3. Record IQ data by running record_orbcomm.py
4. Run file_decoder.py to decode a single recording file (defaults to the first file in the /data folder)
   1. The file it decodes is selected near the top of the file (Line 37). Change it there if you wish to decode other files.
   2. Note: There are 2 data files that come with this repo. If you want to process your own recordings, you'll need to remove those files (or just point the file_decoder.py script to your files).

EXAMPLE OUTPUT
Filename: ./data/1552071892p6.mat
Timestamp: 1552071892.600117
Data collected on: 2019-03-08 19:04:52.600117
Satellites in recording: orbcomm fm114
SDR Sample rate: 1228800.0 Hz
SDR Center frequency: 137500000.0 Hz
Satellite frequencies: 137287500.0, 137737500.0
Remaining frequency offset after doppler compensation: -141.0 Hz
Number of possible packets: 100.03125
Bit stream offset: 3

List of packets: (### indicates checksum failed)
### Unrecognized packet: 9F193958A56A1A7A9BE0ED2B
Fill: data: 19F1D8528E1EF9701DED
Fill: data: 5A8C1A5E354CE775C6A3
Fill: data: 6FE4A5F1DDC8B12CADE5
Fill: data: 567DC3683187453D728D
Fill: data: 463E5D5FB36A15E68001
Message: msg_packet_num: 0 msg_total_length: 2 data: 001F05CE01C0721828
Message: msg_packet_num: 1 msg_total_length: 2 data: 507102000000000032
Message: msg_packet_num: 0 msg_total_length: 2 data: 1167036942905C869C
Message: msg_packet_num: 1 msg_total_length: 2 data: C10183D10BE0A32C54
Message: msg_packet_num: 0 msg_total_length: 3 data: A241000129687B035E
Message: msg_packet_num: 1 msg_total_length: 3 data: 921E026637E0228277
Message: msg_packet_num: 2 msg_total_length: 3 data: A236830000000000F7
Message: msg_packet_num: 0 msg_total_length: 2 data: 836B01E54270B20226
Message: msg_packet_num: 1 msg_total_length: 2 data: 734502B42B00000048
Fill: data: B3489015957F14F39CC3
Fill: data: D9B2B6A2EB952C9A23AD
Unrecognized packet: 0B01FD24CCCCCC204501CF3A
Sync: code: 65A8F9 sat_id: 2C
Downlink_info: msg_packet_num: 0 msg_total_length: 3 data: 27310750A005640094
Downlink_info: msg_packet_num: 1 msg_total_length: 3 data: 7D000BB89010130195
Downlink_info: msg_packet_num: 2 msg_total_length: 3 data: 1D011400000000003F
Network: msg_packet_num: 0 msg_total_length: 1 data: 7800010000000000E2
Ephemeris: sat_id: 2C data: 98E3D5043B9BC34CDDF04C3CE66F98D5A307FB07E1D8
	Current satellite time: 2019-03-08 19:04:53 Z
	Lat/Lon:        44.9555, -116.0878, Altitude:  715.3 km
	Ephem Lat/Lon:  44.7855, -116.0779, Altitude:  715.2 km
Unrecognized packet: 0B011C2AEDEEEE409B02A761
Unrecognized packet: 0B01641D76989944450169D9
Unrecognized packet: 0A48B99524C221A30012BCE8
Unrecognized packet: 0A4C3F01207164CF01127E15
Unrecognized packet: 0A506D28227274970012FF61

Real-time recording and decoding

1. First run the update_orbcomm_tle.py script to get the latest two-line elements for the ORBCOMM satellites.
2. Update latitude and longitude of your receiver in CONFIG.py
3. Run realtime_receiver.py
   1. If there is no satellite overhead it will tell you how long the wait is.
   2. I recommend you use gPredict to know where the ORBCOMM satellites are.
   3. Note that not all the ORBCOMM satellites still transmit. Look in sat_db.py to see the active ones.

DSP Training

In the dsp_training folder are a number of scripts that I used to help me understand the DSP that I needed to decode the ORBCOMM signals. The scripts are simulation only and help understand phase recovery, timing recovery, creating symbols from bits, mixing, filtering, etc.

Scripts

Scripts include:

• sat_db.py: just a dictionary of ORBCOMM satellites I know are active
• orbcomm_packet.py: a list of all the known ORBCOMM packet types and their components
• helpers.py: a file with useful helper functions
• plot_recording_waterfall.py: plots a waterfall of recordings
• update_orbcomm_tle.py: downloads the latest ORBCOMM tles from celestrack.com
• record_orbcomm.py: records ORBCOMM satellites when they are overhead with an RTLSDR
• file_decoder.py: If you have .mat files in the data folder, this script will attempt to decode one
• realtime_decoder.py: This is a class for doing decoding of a realtime stream of samples
• realtime_receiver.py: This is a script that does realtime decoding of the ORBCOMM signal, plus some interesting plots

References

I used these two resources as my primary references.

http://mdkenny.customer.netspace.net.au/Orbcomm.pdf
http://www.decodesystems.com/orbcomm.html

Data format

In the data folder is a couple files of samples that I have recorded.

The files are .mat files. They can be opened with MATLAB or Python (using SciPy's loadmat function).

The files include metadata:

• fc: center frequency
• fs: sample rate
• sats: a list of the names of the satellites overhead
• tles: a list of lists of the tle lines for each satellite (in the order of the sats list)
• timestamp: unix time of the start of the recording
• samples: a numpy complex64 array of the samples
• lat: the latitude of the receiver when the samples were recorded
• lon: the longitude of the receiver when the samples were recorded
• alt: the elevation of the receiver when the samples were recorded

Look at the file_decoder.py script to see an example of how to access the metadata.