The Doppler Wind Experiment in the Optical Communications Era

Kamal Oudrhiri, Sami Asmar and Bruce Moision

June 20, 2013International Planetary Probe Workshop – San Jose

© 2013 California Institute of Technology. Government sponsorship acknowledged.

1. Radio Science (a brief background)

2. Doppler Wind Experiment (as an example)

3. Channel model for intensity-modulated optical signaling and photon-counting detectors

4. A comparison between radio science and optical science

Parameter estimation via optical signals

2

The Start of Radio Science

3

• It became apparent with early missions that occultations by planetary atmospheres would affect the quality of radio communications

• One person’s noise is another’s data

• One can study the atmospheric properties– And other aspects of planetary science,

solar science, and fundamental physics

• A recognized field of solar system exploration with instrument distributed between the spacecraft and the ground stations

Radio Science Investigations

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• Utilize the telecommunication links between spacecraft and Earth to examine changes in the phase/frequency, amplitude, and polarization of radio signals to investigate:– Planetary atmospheres– Planetary rings– Planetary surfaces– Planetary interiors– Solar corona and wind– Comet mass flux– Fundamental Physics

• The measurements are conventionally made at the earth station.

Fundamental Limits on Sensitivity

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1. Frequency stability

2. Amplitude stability

3. Signal to noise ratio

4. Intervening media

5. Spacecraft pointing stability and non gravitational forces

6.Navigation accuracy in predicting & reconstructing trajectory

Radio Science Experiment Types

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• Propagation– Study media– Remove the effects of forces

• Gravitation– Study forces– Remove the effects of media

• Observed changes can be very small

Radio Occultations

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• Study properties of planetary media along propagation path– Atmosphere: temperature-pressure profile– Ionosphere: electron density– Rings: particle structure and size distribution– Byproducts: planetary shapes

• Observables:– Amplitude and phase

• Refraction

• Scattering

• Edge diffraction

• Multi-path

Gravity & Planetary Interiors

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• Determine the mass and mass distribution– GM of body or system (planet + satellites)– Gravity field: higher order expansion of mass distribution

• Constrain models of internal structure– Examples: ocean on Europa

• Improve orbits and ephemeredes• Observables:

– Doppler and range: precise measurement of relative motion• Doppler accuracy to ~ 0.03 mm/s at X-band and few microns/s at Ka-band

• Ranging accuracy to ~ 1 meter

Wind Profiles

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• Deduce wind speed and direction from Doppler when probe descends into atmosphere of planet or satellite

– Huygens Probe at Titan

– Galileo Probe into Jupiter

– Russian probes at Venus

• Configuration:

– Stable oscillators on probe and orbiter

– Spacecraft-to-spacecraft links

– May be able to receive signal on Earth

• determination of Titan‘s zonal wind speed along Huygens descent path

Huygens Doppler Experiment

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Cassini

Probe Support Avionics

TCXOReceiving

Channel BTransmitting dataCarrier not stable

Channel ATransmitting data

Carrier stable

EarthRadio Telescopes

Receiving stable carrier

“Channel A on Earth”

Probe Support Avionics

RUSONot Receiving

2098 MHz RCP

2040 MHz LCP

Direction: ~ 30 degreesLight Time: ~ 1 hr 7 min

SNR: ~ 7 dBcOutside DSN band

Zonal Wind Retrieval

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LSCEWNSdesLS nvvvvv

)(

)coscoscos(cos

1NSNSdesdesCCLS

DWC

EW vvvvv

0fc

vf

LS

R Doppler shift: where

DWE Results

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• Zonal winds West to East

• Turbulent above 100 km

• Strong wind: Maximum ~ 430 km/hr

• Shear layer 60-100 km (10-50 mbar)

– Strong positive/negative wind shear unexpected but evident in some GCMs

• Significant structure in lowest 5 km

• Huygens drifted 3.58º (158.3 km) eastward

• Wind results have implications for super rotational cyclostrophic flow

• Tracking phase, frequency, and power of received signal enables: – spacecraft operation (range, velocity, power)– remote sensing – planetary science

• Future deep-space communications link may be at optical frequencies• How accurately can we track the phase, frequency, and power of the

optical signal?

Science from a spacecraft

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range:Velocity (from doppler):power fluctuations:

Science from an optical pulse train

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Laser Transmitter

Incident Power

time

Photon-counting photo-detector

Photo-Electric Current

time

• Use intensity modulation to transmit a train of pulses

• Detect light with a photon-counting detector, producing an impulse train corresponding to photo-electron arrival times

• Rate of photo-electrons is given by incident light intensity

• Estimate parameters of pulse train from photon-electron arrivals: phase, intensity, and frequency

How well can we estimate phase, power, and frequency of an optical signal and how does this compare to estimation of analogous parameters from an RF signal?

• Deep space optical communications links utilize intensity modulation and photon-counting

– Power efficient with weak signals, not as sensitive as phase modulations to transmission through atmosphere

• We assume pulse train is provided by the communications link– Low duty cycles

– High peak to average power ratio

• We assume pulse train pattern is known– Either from dedicated transmission time or reliable decoding of telemetry

The Optical Communication signal

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Typical duty cycles: 1/16 to 1/256 Incident photon flux (power)

Measured photon arrival times

Signal photons

Noise photons

• Radio-Frequency (microwave)– Phase modulation (BPSK)– Coherent detection– Thermal noise limited– Small energy/photon– Large photons/pulse– Gaussian statistics

• Optical-Frequency (infrared)– Intensity modulation (pulse-position-modulation)– Non-coherent detection– Shot-noise limited– Large energy/photon– Small photons/pulse– Poisson statistics

Radio- versus optical-frequency communication

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Deep Space RF and Optical Communications links use different modulation and detection schemes and have different statistical models.

RF and Optical Parameter Estimation

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Fundamental behavior is the same: differences depend on relative Power, Bandwidth, Noise

Power Noise Bandwidth

• Assume representative values for an RF and optical (intensity-modulated+ direct-detection) Earth-Mars downlink link budget

RF versus optical: comparison of link budgets

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link equations: Ranging subcarrier mod. index

Example: Optical/Ka-band: 32 dB gain in received power term, 16.5 dB loss in noise term, 54 dB gain in bandwidth term relative to range clock, 11 dB loss in bandwidth relative to carrier

RMS errors go as the square-root: expect ~35 dB gain in range estimate, 8 dB gain in power estimate, 35 dB gain relative to range clock frequency,

• Downlink (one-way) Estimation Error, Ka-Band

RF versus optical: performance comparison

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range frequency

power

• Several orders magnitude gain in range estimation error

• Fractional frequency error worse relative to carrier, better relative to range clock

• 8 dB gain in power estimate

~37 dB~37dB

~8dB

Power estimate doesn’t benefit from bandwidth gain

Estimate from 1 MHz range clock

Estimate from 32 GHz carrier ~8dB

• Downlink (one-way) Estimation Error, S-Band, X-Band, Ka-Band, Infrared (optical)

Doppler as a Function of Carrier Wavelength

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• We see gains over S, X-bands, loss relative to Ka-band• Performance illustrated is power-limited error over one-way downlink.

Complete comparison requires characterization of end-to-end optical Doppler link. However, results illustrate feasibility of utilizing optical communications link to extract Doppler measurements.

8.4 GHz (X-band)

Estimate from 2.3 GHz carrier (S-band)

32 GHz (Ka-band)

frequency• To isolate dependence on

carrier frequency, we held all other parameters constant (transmit, receive diameters, noise power)

• Two losses: smaller received power, and loss due to bandwidth reduction 1.55 m (infrared)

• Presented framework for parameter estimation of intensity-modulated signal with photon-counting receivers

– Represents current designs for deep-space optical communications link

• Compared Optical and RF one-way parameter estimation accuracy– Represents one component of range, Doppler, or power estimation– Illustrated large gains in range and power estimation– Gains in frequency (Doppler) estimation relative to S, X-bands, loss relative to Ka-band (for ideal systems in

all cases)

Conclusions/Discussion

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Backup

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• Parameter estimation in radio frequencies utilize pure-tone signaling and coherent detection– Estimates based on observing a sinusoidal signal embedded in additive white Gaussian noise

• We consider parameter estimation from intensity-modulated (coherent state) optical waveforms and direct detection

– Estimates based on photon arrival times given by a Poisson point process

Radio- versus optical-frequency parameter estimation

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Parameter estimation utilizes same capability as communication link.