SAR Flashcards

1
Q

SAR is what type of looking? Normal incidence angles?

A
  • Side-looking

- Normally 20 - 50 degrees

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2
Q

How does SAR achieve spatial resolutions of less than 10m?

A
  • Aperture synthesis
  • Forward motion of craft and sensor’s ability to store target location = larger effective aperture length, or synthetic aperture
  • Antenna ‘smears’ itself across Earth surface, remembers targets = increased spatial res
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3
Q

SAR has what type of measurements?

A
  • Echo (amplitude)

- Phase (timing)

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4
Q

In pixel form, the core SAR image product is called what? Contains how many data values for every channel?

A
  • Single-Look Complex (SLC)

- 2 data values for every channel, Amplitude and Phase

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5
Q

What does a channel refer to in SAR?

A
  • Each transmit and receive polarization combo that the SAR is capable of acquiring
  • eg HH and HV
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6
Q

Phase measurements

A
  • Timing of phase cycles or ‘clock time’ (wavelength peak to peak?)
  • Does not form intuitive image like amplitude
  • Valued for more advanced applications like interferometric SAR and Polarimetric SAR
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7
Q

What range are SAR images collected?

A
  • Slant range

- Must be converted to ground range to get proper image

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8
Q

Slant range

A
  • Distances are measured between the antenna and the target
  • Not ground distances
  • Radar is essentially a ranging instrument measuring distances to objects and sigma naught in slant range
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9
Q

Ground Range

A
  • Distances are measured between the platform ground track and target
  • Placed in the correct position on the chosen reference frame (projection) when processed into an image
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10
Q

What does the slant range vs. ground range configuration lead to?

A
  • Compression of imaged surface information in the near-range
  • Leads to distortions that are large in the range direction
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11
Q

What are the 3 types of major distortion?

A
  • Foreshortening
  • Layover
  • Shadowing
  • Mainly caused by topographic variations and are called relief distortions
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12
Q

Where is compressional distortion most emphasized?

A
  • Near range compression in slant range
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13
Q

Foreshortening

A
  • Compression of topography in scene which are tilted toward the radar
  • Found in mountainous terrain
  • Radar beam reaches 2 different points in elevation at the same time, therefore appears in same position
  • Ex. beam in slant range reaches base of slope before or at same time as top
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14
Q

Layover

A
  • Extreme foreshortening
  • Tall objects are displaced towards the radar due to their shorter distances in slant range relative to ground
  • Slant beam reaches top before it reaches bottom, makes further point appear closer than positions that are nearer
  • Features lean toward sensor
  • Common for mountains and always occurs for buildings (90 degree angle)
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15
Q

Shadowing

A
  • Areas on the ground not illuminated by radar
  • Leaves dark tone in imagery
  • Occurs along range direction behind tall objects
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16
Q

Detected format

A
  • Name for SAR images provided in ground range corrected format
  • Still subject to relief distortions, especially mountains, even after correction
  • True correction would require correction at each data point for local terrain slope and elevation –> big task
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17
Q

What are the 2 SAR modes of operation

A
  • Sensor modes

- Beam modes

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18
Q

What are the 3 main sensor modes?

A
  • Single-beam, also called strip map
  • ScanSAR
  • Spotlight
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19
Q

Single-beam

A
  • Wide range of incidence angles
  • Image quality is balance between fine resolution and wide coverage
  • Wide swath = low spatial res, narrow swath = higher res
20
Q

ScanSAR

A
  • Very wide swath at expense of spatial resolution
21
Q

Spotlight

A
  • Highest spatial resolution
  • Mechanical steering of antenna allows coverage of a specific target area (squint angle)
  • Spotlight allows sensor to build up high spatial res
  • ‘Dwells’ on target, gets more energy, sent and received from target
22
Q

Spotlight: Squint Angle

A
  • Enables radar beam to ‘dwell’ on a footprint for a longer period of time
  • Uses more pulses and increases spatial resolution w/in a footprint
  • More pulses = higher spatial res
23
Q

T/F: One SAR has several beam modes for each sensor mode?

A

True

- Eg Radarsat-2: Sensor modes spotlight, single beam, ScanSAR

24
Q

Beam mode vs. nominal swath width

A
  • Spotlight = finest resolution
  • Then single beam w/ many beam modes from ultra-fine to wide
  • Then ScanSAR w/ narrow and wide
25
Name some examples of Singlebeam modes
- Ultra-fine, fine quad, standard quad, wide standard quad, wide fine quad, fine, multi-look fine, extended high extended low, wide
26
Radarsat-2 Beam modes
- All available as right or left-looking - Ultrafine, Standard beams, standard quad-pol (reduced swath width), Wide swath beams, Fine resolution beams multi-look fine resolution, fine quad pol, ScanSar (wide, narrow), Extended beams (high or low incidence)
27
Spotlight vs ScanSAR resolution
- Spotlight = 10x20km, .8m x 2.5m res | - ScanSar wide = 500km x 500km, 100m res
28
Arctic SAR application
- Safe Navigation through ice - Wide swath not a problem - Can't measure ice thickness but tone/texture can be used to determine old from new ice (old more dangerous to navigate) - Colour code for Nav maps - Sentinel-1 (free) or Radarsat-2 (restricted access, pay)
29
What other simple applications are there for SAR?
- Arctic sea ice, forests, fires, EQ's
30
Speckle
- Real but noise-like process produced by imaging radars which degrades radar image quality - Results in bright and dark (high and low) variations that masks the true BS of the surface - Same cover type may have high and low pixel values - Appears as grainy salt/pepper textured appearance
31
What causes speckle?
- System phenomenon - Caused by constructive and destructive interference of waves returning to radar from scatterers on surface - Constructive when wave peaks coincide, destructive when peaks and valleys coincide - Constructive = bright (additive from peaks) - Destructive = dark (average high and low peak/valley to nothing)
32
What is a major downfall of speckle?
- Reduces ability to identify targets and separate classes | - Eg. classification of land-use
33
What are the 2 methods of speckle removal?
- Multi-look processing | - Speckle filtering
34
Multi-look processing
- Done during image formation - Independent 'looks' at the same scene are averaged to reduce variations due to speckle - Reduces speckle at the expense of spatial res - Speckle may still appear in processed SAR image
35
Radarsat-2, how many looks for beam modes?
- More looks for coarser resolution modes e.g. ScanSAR has 4 x 4, Fine beam has 1x1
36
Speckle filtering
- Spatial filter applied during image processing chain | - Loss of spatial resolution linked to spatial filter (not averaging of looks like multi-look)
37
What is the image processing chain?
- Calibration, speckle filter, geometric correction, display, etc.
38
Speckle Filtering: Kernel
- Chosen filter moves pixel by pixel through an image and changes a particular pixel's brightness value based on function which utilizes values w/in kernel surrounding pixel
39
Speckle Filtering: Larger the kernel =?
- Larger kernel = smoother result - Larger kernel = more loss of spatial detail - User can choose filter size, but must keep this in mind
40
What should an ideal speckle filter keep in mind?
- Homogeneous image areas: Filter should preserve radiometric information, BS intensity, and the edges btwn different areas - Textured image areas: Filter should preserve radiometric information and spatial signal variability (patterns of BS that relate to scene elements)
41
Speckle Filtering: What does averaging do?
- Causes blurring between edges and loss of real textural components - Averaging not always effective for speckle reduction
42
Speckle Filtering: Adaptive filters
- Used to preserve image detail | - Reduce some speckle while accurately preserving radiometric information, edges and texture
43
What is the perfect way to choose a filter type?
- No single solution for which filter type or kernel size - Experimentation needed - Boundaries important? Then examine various algorithms relative to problem, try different kernels
44
Speckle Filtering: Median filter
- Center pixel in kernel is replaced w/ median value of all pixel values w/in the kernel - Effective at suppressing speckle noise while preserving texture and edges
45
Speckle Filtering: Enhanced Lee Filter
- More advanced filter - Pixels designated as homogeneous, heterogeneous, and point target by comparing local kernel Coefficient of Variation, to class cut-off values based on Cu, Cmax and number of looks, L - CoV = (SD/Mean), Cu = 0.523/sq. rt L, Cmax = sq. rt (1 +2/L) - Homo if CoV Cu and CoV Cmax, no filtering - Filter replaces the pixel in the centre of a kernel w/ new value based on its designation (homo, hetero, point)