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See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/320427143 Presentation - Effective Transmission Schemes for Bandwidth Limited Satellite Operations Presentation September 2017 DOI:

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See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/320427143

Presentation - Effective Transmission Schemes for Bandwidth Limited Satellite Operations

Presentation · September 2017

DOI: 10.13140/RG.2.2.17294.66885

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4 authors: Some of the authors of this publication are also working on these related projects: Developing new dust trajectory sensor with single channel amplifier View project Hybrid Ablative Development for Re-Entry in Planetary Atmospheric Thermal Protection (HYDRA) View project Manfred Ehresmann Universität Stuttgart

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Florian Grabi

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Georg Herdrich Universität Stuttgart

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Rene Laufer Luleå University of Technology

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IAC-17-IAC-17,B4,3,6,x39641 Effective Transmission Schemes for Bandwidth Limited Satellite Operations

  • M. Ehresmann, Florian Grabi, Georg Herdrich, René Laufer

68th International Astronautical Congress Adelaide, Australia 26.08.2017 26/8/2017

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Effective Transmission Schemes for Bandwidth Limited Satellite Operations

Introduction and technical context Part 1: Block data transmission

  • Bisection scheme
  • Gradient selective scheme
  • Performance evaluation

Part 2: Continuous data transmission

  • Predictive corridor scheme
  • Performance evaluation

Summary and Conclusions

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Introduction and technical context: MIRKA2 / CAPE

26/8/2017 68th International Astronautical Congress Adelaide, Australia

CAPE – CubeSat Atmospheric probe for education

Limited power for transmission Limited visibility for ground stations

MIRKA2 – Micro re-entry capsule 2

Uncertain window for transmission Limited data rate (Iridum –SDB)

MIRKA2-RX Capsule data rate

Maximum data rate 42.5 b/s Average data rate 12.1 b/s Minimum data rate 4.8 b/s

MIRKA2-RX Transmission tests after flight

  • n REXUS19 sounding rocket
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Part 1: Block data transmission

Transmitting a data set is a common case for satellite operations

  • Limited access to a ground station
  • Limited transmission capability of satellite (power)
  • Constraints on antenna pointing (attitude)

Conventional case:  Chronological transmission of data Data set is transmitted by a First In First Out (FIFO) scheme or similar. In case of link break data is lost Potential reasons: Atmospheric conditions, bad pointing, power system overstrain  Reliability problem

26/8/2017 68th International Astronautical Congress Adelaide, Australia

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Part 1: Block data transmission – Bisection scheme

Solution 1: Bisection scheme

Change of order of transmitted data points Successive bisecting of the data set  Does converge to the full set

 Global view is obtained quickly, resolution increases with time

 Is deterministic: Can be hardcoded

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  • Fig. 1. Bisection scheme for an arbitrary signal and corresponding set of data points. Numbers indicate order
  • f transmission of the measured data points.
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Part 1: Block data transmission – Bisection scheme

Solution 2: Gradient selective scheme

Change of order of transmitted data points by local gradient:

𝑕𝑗 = 𝑒𝑧𝑗+1 𝑒𝑦𝑗+1 − 𝑒𝑧𝑗−1 𝑒𝑦𝑗−1 = 𝑧𝑗+1 − 𝑧𝑗 𝑦𝑗+1 − 𝑦𝑗 − 𝑧𝑗 − 𝑧𝑗−1 𝑦𝑗 − 𝑦𝑗−1 .

 Does converge to the full set

 Global view of extremes is obtained quickly, resolution increases with time

 Not deterministic: Index/time stamp of transmitted data point relevant

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Figure 2: Gradient selective scheme for an arbitrary signal and corresponding set of data points. Numbers indicate order of transmission of the measured data points.

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Part 1: Block data transmission – Performance Evaluation

Case: Random linear concatenated functions

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FIFO: Significant loss of data when link is prematurely terminated Bisection:

  • Quick global view
  • Reasonable

convergence at 25%

  • Good convergence at

50 % Gradient selective:

  • Very quick global view
  • Full convergence at

25% Not always (!)

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Part 1: Block data transmission – Performance Evaluation

Case: Random quadratic concatenated functions

26/8/2017 68th International Astronautical Congress Adelaide, Australia

FIFO: Significant loss of data when link is prematurely terminated Bisection:

  • Quick global view
  • Reasonable

convergence at 25%

  • Good convergence at

50 % Gradient selective:

  • Very quick global

extrema view

  • Good convergence at

25%

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Part 1: Block data transmission – Performance Evaluation

Other : Concatenated exponential functions:

  • Not well handled by bisection scheme, due to indifference to extrema

Interesting parts might be skipped.

  • Well handled by gradient selective schemes, extrema covered first

Concatenated sine functions – similar to noisy signals:

  • Well handled by bisection scheme, due to indifference to signal shape.
  • Not well handled by gradient selective scheme, too many sharp gradient

changes.  Signal smoothing recommended.

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Part 2: Continuous data transmission

For most satellite applications the overall transmission data rate is limited. The potential output data rate of all on-board sensors is much greater. Conventional solution: Reduce overall or sensor specific data rates to accommodate the available bandwidth

  • Potential undersampling of some sensors
  • Potential missing of some effects
  • Potential collection and transmission of uninteresting/irrelevant data

“Uninteresting”  Monotonous / similar data to already known data.

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Part 2: Continuous data transmission

Solution: Corridor predictive scheme

  • Minimization of individual sensor data rate
  • Selection for interesting data points
  • Calculate data prediction corridor

 Data inside the corridor is “uninteresting” Coding scheme is known for ground operator  Implicit knowledge about not-transmitted data  Data outside the corridor is “interesting” and is transmitted  Follow-up recalculation of prediction corridor

  • Calculation scheme needs to be light-weight for OBC

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Part 2: Corridor predictive scheme – Linear regression

Simple example: Linear corridors. Calculate linear regression function from initial data set. Slope a: 𝑏 =

σ𝑗=1

𝑜𝑇𝑏𝑛𝑞𝑚𝑓(𝑦𝑗− Ӗ

𝑦) 𝑧𝑗 − ധ 𝑧

σ𝑗=1

𝑜𝑇𝑏𝑛𝑞𝑚𝑓(𝑦𝑗− Ӗ

𝑦)² y-Intersection: 𝑧0 = ധ 𝑧 − 𝑏ന 𝑦 Spine of the prediction corridor: 𝑧𝑇𝑞𝑗𝑜𝑓 = 𝑏 𝑦 + 𝑧0

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Corridor boundaries: 𝑧𝐷𝑝𝑠𝑠,𝑉𝑞/𝑀𝑝𝑥 = 𝑏 𝑦 + 𝑧0 ± 𝑐𝐷𝑝𝑠𝑠 Losses defined by corridor width 𝑐𝐷𝑝𝑠𝑠 Violation condition: 𝑦 > 𝑧𝐷𝑝𝑠𝑠,𝑉𝑞 𝑦 ˅ 𝑦 < 𝑧𝐷𝑝𝑠𝑠,𝑀𝑝𝑥 𝑦 Add robustness with trigger threshold: 𝑜𝐷𝑝𝑠𝑠𝑗𝑒𝑝𝑠𝑊𝑗𝑝𝑚𝑏𝑢𝑗𝑝𝑡 > 𝑜𝑈𝑠𝑗𝑕𝑕𝑓𝑠𝑈ℎ𝑠𝑓𝑡ℎ𝑝𝑚𝑒 Add reliability by defining a maximum interval between selected data points:

𝑒𝑛𝑏𝑦

 Important to determine whether a sensor is broken or nominal “uninteresting”

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Part 2: Corridor predictive scheme – Performance

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Figure 14: Concatenated randomized noisy linear functions input signal with predictive corridor scheme at low sampling rate.

  • Red points are selected for

transmission.

  • Sample size 20
  • Selection and recalculation

after 2nd corridor violation

  • Max distance between points

is 30 300 data points polled 19 selected for transmission  Reduction rate: 15.8 !

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Part 2: Corridor predictive scheme – Performance

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  • Red points are selected for

transmission.

  • Sample size 20
  • Selection and recalculation

after 2nd corridor violation

  • Max distance between points

is 30 3160 data points polled 235 selected for transmission  Reduction rate: 13.4 Higher reduction possible, by increasing gap distance.

Figure 15: Concatenated randomized noisy linear functions input signal with predictive corridor scheme at high sampling rate.

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Summary & Conclusions

Part 1: Block data transmission Bisection scheme: Lossless, signal shape indifferent scheme, deterministic, data reduction of 4 and more possible Gradient selective scheme: Lossless, signal shape selective scheme, not deterministic, noise prone data reduction of 10 and more possible Part 2: Continuous data transmission Predictive corridor scheme: Lossy, signal shape dependent scheme, not deterministic, noise resistant data reduction of 10-25 has been observed, much greater possible

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Other Work, Contact

Effective Transmission Schemes for Bandwidth Limited Satellite Operations

More on MIRKA/CAPE:

  • Communication architecture and operation strategies for the electrically propelled CubeSat and

re-entry capsule system CAPE, 68th IAC, 2017

  • Micro Return Capsule 2 – REXUS Experiment results, Small Satellites Systems and Services

Symposium, 2016

  • Micro Reentry Capsule 2 REXUS, 1st Symposium on Space Educational Activities, 2015

CubeSat-sized Re-entry Capsule MIRKA2, 10th IAA Symposium on Small Satellites for Earth Observation, 2015

  • CubeSat Atmospheric Probe for Education (CAPE), 10th IAA Symposium on Small Satellites for

Earth Observation, 2015 Contact:

  • M. Ehresmann

ehresmann@irs.uni-stuttgart.de Institut für Raumfahrtsysteme Pfaffenwaldring 29 70569 Stuttgart

26/8/2017 68th International Astronautical Congress Adelaide, Australia

  • G. Herdrich

herdrich@irs.uni-stuttgart.de Institut für Raumfahrtsysteme Pfaffenwaldring 29 70569 Stuttgart

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