This document analyzes the characteristic analysis of vehicle targets in quad-polarized Radarsat-2 SAR images. It discusses experiments analyzing differences in backscatter based on incidence angle, azimuth angle, and truck configuration. The results show incidence angle has the largest impact on backscatter characteristics. Polarization decomposition helps verify target characteristics, with double bounce being important for trucks. Vehicles are best detected when parallel to the SAR flight direction. Prior geographic constraints can aid vehicle detection on roads in SAR imagery.

1. CHARACTERISTIC ANALYSIS OF VEHICLE TARGET
IN QUAD-POL RADARSAT-2 SAR IMAGES
Bo ZHANG, Hong ZHANG, Chao WANG
bozhang@ceode.ac.cn
Center for Earth Observation and Digital Earth Chinese
Academy of Sciences

2. Outline
• Motivation
• Experiment data sets
• Truck characteristic analysis methods
• Experiment results

3. Motivation
• High resolution SAR image brings to new application
TerraSAR-X COSMO-SkyMed Radarsat-2
High resolution 1m X-band 1m X-band 3 m C-band
Quad polarization Technical possible × 8m
Special feature Dual-receive-antenna
New application: Traffic monitoring application
Airplane detection & recognition
Vessel detection & recognition
[1] G. Palubinskas, H. Runge. Radar Signatures of a Passenger Car. IEEE TRSL. 2007, 4( 4):644-648
[2] Jean Beaudin, RADARSAT-2 GMTI Project. http://www.ottawa.drdc-rddc.gc.ca/html/RADARSAT_2_GMTI-eng.html
[3] Tom I. Lukowski, Bing Yue, and Karim Mattar. Synthetic Aperture Radar for Search and Rescue:Polarimetry and Interferometry.
IGARSS, Anchorage, AK, Sep. 2004, vol. 4, pp. 2479- 2482.

4. Motivation
• Object characteristic analysis is important for monitoring system
– object detection, discrimination and identification.
SAR image Target detection Target discrimination Target identification Target
Target character vector
Target character vector

5. Motivation
The objective of this research
Traffic monitoring using quad polarimetric Radarsat-2 SAR image under the
condition of disrupted traffic states caused by factors like snow disaster
In this application, vehicles were eager to be slow or static
Image incidence angle
Quad-Pol Image polarization
SAR image
Image polarization
Vehicle Vehicle
Road network extraction RCS analysis Target aspect angle
Target model
GPS
Background roughness
Background material

6. Experiment data sets
• Radarsat-2 Data sets
Image parameters Experiment 1 Experiment 2
Image time March 2009 Sep 2009
Image mode Fine Quad-Pol Fine Quad-Pol
Data format SLC complex SLC complex
Pixel Space (m) 4.93*4.73 4.74*4.73
Incidence angle (degree) 22.16～24.09 38.37～ 39.85
Orbit Ascend Descend
Frequency（GHz） 5.4 5.4
Look number 1 1
Range processing 30.0 30.0
bandwidth(MHz)
Azimuth processing 855 855
bandwidth(Hz)

7. Experiment data sets
Road background
• Experiment 1 • Experiment 2
Material Mixed soil Asphalt
Width 13 24

8. Experiment Trucks
• Experiment 1 • Experiment 2
SAR
SAR
Size(L, W, H) 8.7, 2.3, 3.4 11.9, 2.5,3.8
Truck
Rain cloth Half cover Close cover

9. Characteristic analysis methods
• Vehicle azimuth measure
• Vehicle RCS measure
• Vehicle polarization component measure

10. Vehicle azimuth measure
SAR flight
direction (X) x
Z
Geographic north
Magnetic north
incidencea
angle
y
Aspect angle
SAR strip
Geological compass GPS

11. Vehicle RCS measure
SAR image
Quad-Pol σ0 Truck image
radiometric
SLC SAR image Chip (c,t)
correction
image
Radarsat -2 Segmention with
metadata GPS coordination
∞ ∞
σ =∫ ∫ σ 0 (x, y )dxdy ≈ Δx ⋅ Δy ∑c ,t σ 0 (c, t )
−∞ −∞
△x × △y : represents the area of one pixel in SAR image
∑ c ,t
σ 0 (c , t ) : stands for the integral of surface targets at the position of (c,t)

12. Polarization component measure
• Pauli decomposition
– When the material meet the reciprocity condition
• SPAN

13. Experiment results
• Difference in incidence angle
• Difference in azimuth angle
• Difference at configuration of truck

14. Difference in incidence angle
• Experiment 1 • Experiment 2
• Incidence angle 23.2 ° • Incidence angle 39.7 °
SAR H H SAR
H
H
H H
Fig 3(a). Experiment 1 σ0 of 0 °, 225° and 270°Fig 3(b): Experiment 2 σ0 of 180°, 225° and 270°

15. Difference in azimuth angle
• Experiment 1 • Experiment 2
SAR H H SAR
H
H H
H
Az: 0 ° Az: 225° Az: 270° Az: 180 ° Az: 225° Az: 270°
Figure 4: Target slice of Pauli decomposition and its composition ratio
at Experiment 1(left) and Experiment 2 (right)

16. Difference at configuration
• Experiment 1 • Experiment 2
270 ° 270 °
span image span image
270 °pauli components 270 °pauli components

17. Discussion & conclusion
• The impact placed by incident angle on the backscattering
characteristics of vehicle target is the most significant.
• polarization decomposition technique is benefit for further verify the
characteristics of vehicle target.
– Double bounce is the most important characters to trucks on road.
– Parallel to SAR flight direction is the best azimuth for vehicle detection
• Considering the priori geographic information constraint, detection
and extraction of vehicle target and vehicle cluster can be achieved
under the guidance of simple background as road