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The Cyclone Global Navigation Satellite System is a group of 8 smallsats which will orbit near the equator (inc=30°) and work as a constellation to take data on typhoons and hurricanes. While they are meant to map wind speed they don't actually do that. They measure ocean surface roughness, but they don't even to do that. Each of the eight smallsats will carefully monitor up to four GPS satellite signals, and for each signal the direct beam and the reflected beam off of the ocean will both be measured.

How (actually) will the CYGNSS satellites interpret ocean roughness by comparing direct and reflected signals from GPS satellites? I'm interested in an explanation of how the received signals will be compared to extract a number for ocean roughness.

See these items also:

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above x2: screen shots from CYGNSS_FactSheet_October2014

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  • $\begingroup$ You can tell the height of the ocean surface in this manner by timing how long it takes the signal to return, just like in radar. I assume that each satellite will measure a signal bounced off a certain location. By doing this over several locations, you can figure out how level the ocean is. If it's perfectly flat, each satellite will register the signals as arriving at the same time. Otherwise there will be some difference in altitudes, the difference being the height of the waves. At least, that's what I assume is happening. $\endgroup$ – Phiteros Nov 12 '16 at 17:35
  • $\begingroup$ Let us continue this discussion in chat. $\endgroup$ – Phiteros Nov 13 '16 at 3:54
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Addressing multipath has long been a challenge with regard to GPS. Carrying a GPS-enabled smartphone toward the heart of a large city results in GPS-estimated positions and altitudes that bounce around. The problem is signals reflecting off of buildings, sometimes multiple times. Those reflecting surfaces result in multiple paths that a GPS signal can follow to reach a GPS receiver, hence the term "multipath".

Rather than being confused by multipath, CYGNSS takes advantage of it. Each CYGNSS satellite receives a direct GPS signal that tells the satellite where it is. The satellites also receive multiple indirect signals due to reflections from the surface of the Earth. The spectrum of how those bounced signals trail off over time provide information regarding the local roughness of an ocean's surface. The spectrum of delays from a very smooth surface versus a very rough surface differ markedly.

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  • $\begingroup$ They seem to use a 2D delay vs doppler plot, and correlate roughness with intensities at different delays, where different delays represent different distances away from the specular point. A very smooth ocean surface for example would only reflect close to the specular point, while a very choppy sea with high wave angles could contribute reflections over a larger area and therefore larger spread in delays. But how they do it I don't know. $\endgroup$ – uhoh Nov 14 '16 at 12:55
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The CYGNSS spacecraft will use a technique called "Delay Doppler Mapping". Each satellite will be equipped with a Delay Doppler Mapping Instrument (DDMI), which is capable of receiving four DDM's at once. DDM is only slightly different from standard Radar Altimetry, which measures the distance to an object by tracking how long it takes a signal bounced off the surface to return. That is the 'Delay' part of DDM. When using DDM, you 'look' at the surface of the object for much longer, allowing you to integrate over the full time. This allows the signals to be weaker, because they will be integrated over a longer amount of time. In addition, DDM differs from radar because it uses the Doppler effect to track how fast (and in what direction) something is moving. DDM can be used to calculate how fast the wind is moving at the surface (1), which is one of the main goals of the study. CYGNSS will be using special (and highly complex) algorithms (2) to retrieve the wind surface speed.

In the case of CYGNSS, the signals will originate from orbiting GPS satellites. The satellites will also beam the signal directly to CYGNSS, so that they can compare the reflected response to the emitted signal. This idea was proposed back in 1993 (3). Since CYGNSS consists of eight smallsats, each capable of measuring 4 areas, the mission will be able to reconstruct the shape of the ocean surface and windspeeds there over a significant area.

From the shape of the ocean surface, researchers will be able to infer how rough the ocean is at that particular location. While there have been attempts to create a standard parameter for roughness, there currently is not one in use (as far as I could find). Instead, researchers will rely on factors such as the wave height, spacing, speed, and steepness to determine how rough the surface is. Higher and more closely spaced waves (thus steeper waves) indicate a rougher sea than shallow, long waves.

Emily Lakdawalla does a good job of explaining how DDM is used to get the shapes of asteroids on her blog.

Citations:

  1. Chen Li, Weimin Huang. "Sea surface wind retrieval from GNSS delay-Doppler map using two-dimension least-squares fitting" (2013). DOI: 10.1109/OCEANS-Bergen.2013.6608019
  2. Maria Paola Clarizia, Christopher S. Ruf. "Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System (CYGNSS) Mission" (2016). DOI: 10.1109/TGRS.2016.2541343
  3. Daniel Pascual, et. al. "Precision Bounds in GNSS-R Ocean Altimetry" (2014). DOI: 10.1109/JSTARS.2014.2303251
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  • $\begingroup$ My question is "How with the CYGNSS spacecrafts (actually) measure ocean roughness?" This is just a collection of sentences that skirt the issue. Also, your "Special Algorithms" link requires a privileged login ID. The radar imaging of asteroids is a third and also completely different technique. It only works on rotating bodies that are completely illuminated. You can't just jumble up a bunch of different technologies together and call it an answer. $\endgroup$ – uhoh Nov 13 '16 at 4:58
  • $\begingroup$ My second paragraph: "How (actually) will the CYGNSS satellites interpret ocean roughness by comparing direct and reflected signals from GPS satellites? I'm interested in an explanation of how the received signals will be compared to extract a number for ocean roughness." $\endgroup$ – uhoh Nov 13 '16 at 5:04
  • $\begingroup$ Perhaps I am misunderstanding your question. What are you asking for? How they parameterize ocean roughness? Or what technology they are using to do it? Or are you asking for exactly what mathematical equations and computer programs they use? Sorry about the broken link. Those papers are locked behind paywalls, so I had to use my university library. I'll replace the links with citations or something. $\endgroup$ – Phiteros Nov 13 '16 at 6:56
  • $\begingroup$ @Phiteros It's great to have references ! Please complement the links with citations, not replace then :) $\endgroup$ – Antzi Nov 14 '16 at 2:54
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    $\begingroup$ I thought I fixed them with direct links. I will just replace the links with citations instead. I will also attempt to clarify my answer. From what I have found, there basically is no standard parameterization for surface roughness. Instead, you just infer how rough the ocean surface is from factors like the wave height, spacing, and steepness. $\endgroup$ – Phiteros Nov 14 '16 at 15:29
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This is explained in the mission Science Briefing. Basically, they are measuring the distortion of the GPS signal reflected by the water surface.

On a calm flat surface, the reflection is specular, I.e undistorted. The more rough the surface is, the more the reflection becomes diffuse.

You can observe the same effect if you observe the reflection of e.g. the moon on a calm resp. rough lake surface.

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  • $\begingroup$ The video of the briefing is really helpful - the graphics showing the multiple specular points per satellite and coverage over time really helps. I understand the basics of the delay-doppler plot starting at 09:10, delay is shortest at the specular point (principle of least time) and increases with a sort-of radial gradient (shown as CHIPS), and the doppler variation just comes from the geometry of the rates of change of the different total path lengths, but starting from a series of delay-doppler 2D histograms, how is that processed to arrive at some metric that correlates with roughness? $\endgroup$ – uhoh Dec 14 '16 at 14:40

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