Remote sensing and SAR radar images processing Physics of radar

Remote sensing and SAR radar images processing Physics of radar

TABLE OF CONTENTS Potentialities of radar Radar transmission features Propagation of radio waves Radar equation Surface scattering mechanisms Volumetric scattering mechanisms Penetration depth of waves in observed media

otentialities of radar All-weather observation system (active system). not sensitive to sun lightening, not sensitive to cloud cover Other advantages with respect to optics: ranging (simple and accurate geometric modeling), detection capacity (even at medium resolution) Sensitivity to dielectric properties of medium (water content, humidity), and to its roughness the radar response when the moisture and/or when roughness Penetration capabilities estimation of plant biomass, observation of buried structures, cartography of subsoils, etc. penetration when the frequency Sensititivity to topography (related to the acquisition geometry) Sensitivity to geometrical structures with scales of the same order as the wavelength

ntroduction Imaging radar features Drawbacks: speckle (difficult visual interpretation) Sensitive to: roughness relief (slope) humidity metallic and artificial objects

ntroduction (2/2) Accessibility With respect to optics: day/night imaging capacity (x 2) insensitive to cloud cover ( x 5) 10 times more images available Faster information access Multi-Incidence - Multi-Resolution With a constellation of 4 SAR Satellites : information access delay shorter than 24h (from decision to interpretation)

Radar transmission features The frequency (carrier frequency + bandwidth) f (GHz ) 0.1 1 10 100 Ku Ka X C S L P 300 30 3 0. 3 (cm ) The propagation direction (Ex: ERS: 23 ) The transmitted power (Ex: ERS: ~ 5 kw pic) impact on image quality The polarization vˆ vˆ ĥ kˆ nˆ ĥ kˆ nˆ Horizontal polarization RADARSAT type ĥ Vertical polarization ERS type ĥ

Radar transmission features xˆ E H electric field magnetic field ŷ ẑ kˆ energy propagation Spatial-temporal variations of the electric field during propagation: E ( r, t) E O.exp ( j.( kˆ. r. t)) Configuration of electromagnetic fields in free space: E ( r, t ) H ( r, t ) kˆ E ( r, t), H ( r, t), kˆ form a direct trihedral Propagation of radio waves Maxwell s equations

adar equation (1/4) Case of point targets (1/2) i : incident flux Portion of backscattered power point target i = incident flux = incident power per area unit normal to incident beam: i Portion of backscattered power: Power received on the receiving antenna: Aeff Pemitted Ge. 4R ² P received. i 4 R ² Gr ² 4 Ge: Transmitting antenna gain; R: Radar-target distance i Aeff 4 R Effective area of receiving antenna ² Portion of energy sent back by the point target = Radar reflective area (SER )

adar equation Case of point targets The radar equation is derived from the transmission-backscattering-reception process: P received Pemitted. Ge Gr. 4 R ² 4 R ² 4 ² transmission backscattering reception P received Pemitted. Ge Gr ² 3 4 4 R Target (radar equivalent crosssection) Unit: m² system propagation Set of terms determined by calibration procedures

adar equation Case of extended targets The radar backscattering coefficient (marked σ o ) represents the average value of the Radar eflective area per area unit (case of an extended target, for example on the scale of a pixel): o d If area is homogeneous: ds o S Unit: m²/m² σ is expressed in m², σ o is expressed in m²/m² 0 means normalization in relation to an area o k P received Pemitted Coefficient k is determined by calibration Representation of 0 on a logarithmic scale: o (db ) 10.log 10 ( o ) Unit: dbm²/m² Value dynamics ~ -40 dbm²/m² +10 dbm²/m²

adar equation (4/4) Case of extended targets (2/2) Behavior and typical values of 0 50 dbm²/m² 20 dbm²/m² 0 Point targets: vehicles, ships, etc. Urban areas, etc. 0 dbm²/m² 0 dbm ² / m² 0 0 dbm ² / m² -7 dbm²/m² Forest -10 dbm²/m² Vegetation -15 dbm²/m² Short grass Noise image limit -22 dbm²/m² Concrete, bitumen, etc. 0 0 dbm² / m² 0 0 dbm ² / m² Depends on incidence Depends on frequency

urface scattering mechanisms (3/4) Case of a rough dielectric surface (1/2) medium 1 medium 2 Medium 2 homogeneous: no volume scattering roughness generates backscattering (part of energy returning to the radar). The dielectric nature roduces penetration. The radar backscattering coefficient o (quantity of energy returning to the radar) depends on: The surface roughness The dielectric permittivity of medium (related to the water content) o ~ f (roughness). g ( r ) o when roughness o when moisture hence indetermination: moisture Rough dry soil = Wet smooth soil Indetermination between the moisture and roughness level based on knowledge of 0 alone

urface scattering mechanisms (4/4) Case of a rough dielectric surface (2/2) Quantification of roughness, Rayleigh s criterion: A surface is not intrinsically smooth or ough from the radar point of view. This concept is meaningful only if referred to wavelength. ẑ kˆinc A Rayleigh s criterion: h B When the phase difference between the 2 reflected waves (at A and B) due to propagation is < /2, the surface is considered as smooth. Now: = 2/ = 2/hcos smooth surface if: h < λ/8/cosθ Δ > π/2 rough surface Remark: in C-band (l=5.6 cm), condition (1) gives h < 0.8 cm at 23 (ERS-1): all natural surfaces are rough under these observation conditions.

olumetric scattering mechanisms Case of the forest 1 6 5 1) Crown scattering 2) Trunk scattering 2 7 4 3 3) Trunk-soil interaction 5) Direct soil scattering 4) Attenuated soil scattering 6) Trunk-branch interaction 7) Soil-branch interaction Examples of main backscattering mechanisms on the forest Volume backscattering mechanisms generally rely on interaction mechanisms which are highly complex and still not well-known. Main trends: Backscattering coefficient when vegetation volume (biomass) Wavelength penetration when frequency, i.e. when wavelenght

enetration depth of waves in observed media Penetration capabilities of radar waves versus wavelength L-Band = 23 cm C-Band = 6 cm X-Band = 3 cm 1 m 6 m 20 m SIR-C image Landes Forest, France L-Band, 26 ( 0 HV) High penetration capabilities in canopy. Application: Biomass cartography (CESBIO origin )

RADAR SENSITIVITY TO BIO-MASS vv (dbm 2 /m 2 ) -6-7 -8-9 -10 vv (dbm 2 /m 2 ) -2-4 -6 o -11 o -8-12 -14 0 33 65 95 130 150 Biomass (tons/ha) L-band, VV-polarisation, 26-10 0 33 65 95 130 150 Biomass (tons/ha) C-band, VV-polarisation, 26 o hv (dbm 2 /m 2 ) -16-18 -20-22 -24 0 33 65 95 130 150 Experimental results show that radar sensitivity to biomass is a complex mechanism depending jointly on frequency and polarisation Biomass (tons/ha) L-band, HV-polarisation, 26 SIRC data, Landes forest, France (origin : CESBIO)

enetration depth of waves in observed media Radar signature differences between X-band (10 GHz) and L-band (1.25 GHz) X-Band ESAR L-Band ESAR The visibility of a grass runway in the right image demonstrates the volumetric scattering characteristics (thus the enetration characteristics) in L-Band. For the same reason, forest plots are brighter in L-Band. Surface roughness is etter reflected in X-band. Also apparent is the rather low image constrast in X-Band as compared to L-Band.. rom: http://atlas.op.dlr.de/ne-hf/projects/esar/igars96_scheiber.html

enetration depth of waves in observed media Capabilities of low-frequency imaging radars (P-Band) Centimetric wavelength (2 cm) S-Band Metric wavelength (290 cm) P-Band he right image is an example of low-frequency radar imagery acquired in the P-Band (100 MHz). lthough of lower image quality compared to the left image, it makes it possible to see underground tructures, in this case pipeline segments (VNIIKAN Siberian campaign -1994)

Left: SIR-C multi-frequency radar image (Nile) (R : CHH, G : LHV, B: LHH). Inverse LUT 18 Below: Wave penetration in bare soil for different SAR bands as a function of humidity bande L bande C bande X 16 14 From : www.jpl.nasa.gov/radar/sircxasr penetration ( cm ) 12 10 8 6 4 2 0 0 10 20 30 40 50 60 Soil humidity ( gr/cm 3 ) Left: IR optical image over the same region RADAR SOIL PENETRATION

The speckle noise, consequence of a coherent illumination (1/2) pixel n 1 m pixel n 2 m e e contribution of pixel response one scatterer

The speckle noise, consequence of a coherent illumination (2/2) Large radiometry : large noise The speckle noise is a multiplicative noise Low radiometry : low noise Image SETHI, bande C, 3 m

SAR principle / Image Quality / Processing

CONTENT Introduction Reminders: detection radar / antenna scattering Side-Looking Airborne Radar (SLAR) Range processing Synthetic Aperture Radar (SAR) Azimuth processing SAR ambiguities Moving targets Special modes (SAR) Image Quality: Radiometry Image Quality: Geometry Image Quality: localization Processing at CNES: PRISME

eminder: Detection radars target azimuth azimuth range Range range Pulses Radar screen The range information comes from the time needed by the pulse to travel way and back 0 Pulse transmission chronogram t

eminder: Antenna scattering L L Wavelength Angular aperture (horizontal plane) Antenna length (horizontal direction) L ' The larger the antenna, the narrower the aperture (resolution ) Numerical example: L 4m, R 4 km (airborne radar), 3 cm (X band) resolution 30 m

LAR: Side-Looking Airborne Radar (1/9) s Azimuth direction Range direction Linear displacement of the antenna along the track (aircraft) Pulses

LAR: Why «Side-Looking»? (2/9) Removal of Left/Right Range ambiguity Left/Right Range ambiguity r range r azimuth 3D representation

LAR (3/9) Azimuth resolution Prf: Pulse Repetition Frequency L s Azimuth direction Numerical example: (airborne example) W Chronogram: pulses versus time H Echoes Range direction Transmitted pulse L = 4 m W = 5 cm = 20-60 H = 3000 m Swath = 4 km R azi = 25-45 m Azimuth resolution: Rθ, with L SLAR azimuth resolution 35m Remark: Azimuth pixel size = S / Prf Swath R azi

LAR (4/9) Ideal range resolution: Case of a Dirac pulse transmission Transmitted pulse (Dirac) ideal time resolution Sampling of the received echo (with Fs frequency) = sampling in the spatial domain (generation of an image line) c 2Fs : range (distance) pixel size in the radar geometry, by construction of an image line c 2 Fssin : ground range pixel size In the case of a Dirac transmission, range resolution = pixel size in range: it depends only on the sampling frequency Fs. This is always true for the range pixel size (by construction), but not for the resolution if the pulse is not a Dirac

LAR (5/9) Real range resolution: case of a pulse transmission of duration (1/2) Practically, for power budget reason, the pulse duration is. The resulting resolution is dominated by the actor c as shown in next slide 2 1/ PRF Pulse duration distance (or range) resolution: c /2 and ground range resolution: (Numerical example ERS, 37 s, range resolution 5 km) c 2sin

LAR (7/9) Improvement of range resolution: pulse compression In order to improve distance resolution, the transmitted pulse is frequency modulated (over a bandwidth chirp): this can be shown to be equivalent to the transmission of a shorter pulse: Modulation bandwidth: chirp B comp comp 1/ B chirp equivalence 1/ PRF 0 1/ PRF t Numerical example ERS, 37 s, B chirp =15.5 MHz comp =64 ns Achieved range resolution (slant range): Achieved range resolution (ground range): Re s Res dist dist _ sol c 2. B 2. B chirp chirp c.sin( i) i / sin( i)

LAR (8/9) Pixel size vs. Resolution in range Compressed Pulse duration comp t0 resolution t1 t2 time Numerical example: ERS Fs 18. 96 MHz Pixel slant _ range 7, 9 m Pixel ground _ range 26 to 18 m swath B 1 comp 15. 5 MHz m c 2 Fssin c 2Fs Pixel size The pixel size is defined by the sampling frequency Fs The range resolution is defined by the modulation Bandwidth B chirp Res slant _ range 9. 7 Resground _ range 22 to 32 m The pixel size is generally built slightly smaller than the resolution: FsBchirp

ynthetic Aperture Radar (SAR) Principle (1/12) Pulse transmission v Azimuth direction The antenna progression along the orbit allows to observe each given point at different times Range direction Resolution improvement in the azimuth direction

AR Principle (2/12) Signal processing in azimuth: principle (1/2) illumination duration v L illumination duration v v azi Equivalence SAR Synthetic Aperture The moving small antenna is equivalent to a long fixed antenna (size, directivity, resolution ) T T ' azi S Coherent adding of successively received echoes T T ' Resolution gain in the azimuth direction (Ex: ERS: 5 km 5 m) he compression rate Na equals the number of coherently added echoes (complex addition). It is he resolution gain in the azimuth direction

AR Principle (4/12) Signal processing in azimuth: Doppler analysis (1/5) The range variations between a target and the sensor produce a linear Doppler effect of the transmitted pulse (quadratic distance&phase variations with time linear frequency variations with time in a frequency band: Doppler Bandwidth) Fd > 0 Fd = 0 Fd < 0

AR Principle (5/12) Signal processing in azimuth: Doppler analysis (2/5) illuminati on duration L :T int v Doppler frequency f dop 1 2 d dt where: R azi Instantaneous phase Total Doppler bandwidth f dop B dop 2 R ² v ² 1 / 2 0 2 t ² v ² t 2 R v ² T 2 R int T int R L 1 v Position origine des temps T T S azi ' R R L B dop 2 spatial v L resolution v Bdop L 2 Target-antenna range variations during the illumination time produce a Doppler effect, resulting in spreading the backscattered energy over a bandwidth B dop 2 v L

AR Principle (6/12) Signal processing in azimuth: Doppler analysis (3/5) v forward look central look Frequency spectrum in azimuth (antenna pattern modulation) backward look S ( f ) azi f f dop B dop T int / 2 T int / 2 t B dop Doppler excursion versus time (case of a zero Doppler centroïd) f dop v ² t 2 R T int

mage quality: geometry (1/4) radar versus optics radar acquisition: range discrimination of the space: A,B,C (From Elachi, 1989) optical acquisition: angular discrimination of the space: A,B,C

mage quality: geometry (2/4) geometrical artifacts related to the vision in range The foreshortening effect radar Radar discrimination capacity (From Elachi, 1989) shortening of slopes facing the radar stretching of slopes oppositely oriented to the radar

mage quality: geometry (3/4) geometrical artifacts related to the vision in range The layover effect Radar trajectory Look direction A shadow A B B he point A (top) is projected before B (base) in the direction of the radar pass Layover effect on airborne image Sethi Tour Eiffel, Paris, C band (resolution: 3m)

mage quality: geometry (4/4) geometrical artifacts related to the vision in range example of foreshortening, layover and shadows Standard beam position 1: acquired Feb.12, 1996 From: RADARSAT Geology Handbook (RADARSAT International), 1997

ENVISAT MERIS Not quite the same geometry!! Where is Spain?Where is the North? Where did the satellite pass????