Radar Imaging Processing

The topics presented here are:

See also:
Reading Images at SPRING
How to register an image?
Image Processing Techniques.


Introduction to Radar Image Processing

The term Radar ("Radio Detection And Ranging") has been used as a generic form to classify systems that operate in the microwave frequencies.

These systems were initially used for militaries purposes during the Second World War and, later, for civilian uses starting in the 70th decade.

The increasing utilization of microwaves imaging techniques is due to the own characteristics of the imaging systems, in which the spectral region of operation allows the high transmission of electromagnetic waves in the atmosphere independent of the solar illumination, even when the atmosphere is cloudy or during precipitations, being possible to generate images under adverse conditions.

The transmission of electromagnetic waves by a medium is directly proportional to the wavelength; therefore, the smaller the radar frequency the greater is the degree of penetration. This facility permits imaging where optical and infrared imaging systems are inefficient, especially in situations of extensive cloud cover, as it is the case of Amazon region.

The following figure presents the percentage of wave transmission, by wavelength, containing the visible, infrared and microwaves regions.

radar_01.gif - 38848 Bytes

The degree of penetration depends on the target moisture, on the vegetation density, as well as on the wavelength. Therefore, shorter wavelengths interact with surface vegetation layers, and longer wavelengths interact with sub-surface vegetation layers, being possible, in some cases, to interact with the soil or even with the subsoil. radar_02.gif - 35746 Bytes                  

Figure - Radar signal penetration in vegetation. Source: Ulaby et al (1981a), p.4.

While in the optical spectral bands the interaction occurs at the molecular resonance level in the surface contact, in the microwaves the backscattering is conditioned to the geometry and to the dielectric properties of the surface.

The combination of microwave and optical images permits a better understanding of the objects, allowing the inference of their different properties.

The radar systems may be grouped in imaging and non-imaging systems (Ulaby et al., 1981a). The imaging systems include the rotating antenna systems, the side looking real aperture radar (SLAR), and the side looking synthetic aperture radar (SAR). Among the non-imaging radars, it can be mentioned the scatterometers, the spectrometers and the altimeters.

Systems and Applications

The SLAR-RAR (Side Looking Radar of Real Aperture) radars were the first microwave imaging system, which were used during the II World War as auxiliaries for nocturnal bombardment.

The SLAR has an antenna that illuminates laterally the targets with a beam which is vertically wide, and horizontally narrow. The sweep for image generation is produced by the movement of the aircraft during its passage over the area to be covered. This radar has the inconvenience of having the azimuth resolution directly proportional to the distance of the antenna to the object, and inversely proportional to the used wavelength.

With the advent of the Synthetic Aperture Radar (SAR), developed in the 50´s, this problem was solved since the azimuth resolution of this system is independent of the distance of the radar to the object to be imaged.

The civilian use of the system started in the 70´s, when some programs were carried out using radar systems on board of aircrafts.

The use of orbital radar began with the launching of SEASAT in 1978, and based on its data, NASA started the SIR ("Shuttle Imaging Radar") Program, which consisted of a series of short duration flights. Inside this program it was launched the SIR-A (1981), SIR-B (1984) and SIR-C (1994). Longer missions started with the launching of ALMAZ-1 in 1981, ALMAZ-2 in 1991, ERS-1 in 1991, JERS-1 in 1992, ERS-2 in 1995 and RADARSAT in 1995.

Radar can be used for several environmental applications, such as:

Geology:

  • Analysis of geological structures (fractures, faulting, folding and foliations); lithotypes, geomorphology (relief and soils) and hydrography for mineral resources researches;
  • Evaluation of the potential of superficial and underground hydrological resources;
  • Identification of areas for mineral prospecting.

Agriculture:

  • Agricultural planning and monitoring;
  • Identification, mapping and inspection of agricultural crops;
  • Soil moisture determination; irrigation systems efficiency.

Cartography:

  • Planimetric mapping ( 1:20.000 and 1:50.000 scales);
  • Altimetric mapping (interferometry).

Forestry:

  • Forest planning and monitoring;
  • Determination of forest classes;
  • Identification of the actions of some diseases;
  • Deforestation mapping;
  • Identification of selective logging areas;
  • Biomass estimation.

Ice and Snow:

  • Ice mapping and classification;
  • Defrost/flood monitoring.

Hydrology:

  • Management and planning of hydrological resources;
  • Soil moisture detection;
  • Interpretation of hydrological parameters: transmissivity, flow direction, permeability, discharge, etc.

Environment :

  • Environmental planning and monitoring;
  • Identification, evaluation and monitoring of Hydrological resources and of environmental physical processes (silting, erosion, soil slipping, etc.)
  • Identification and analysis of environmental degradation caused by mining, waste disposal, anthropic activities, etc.;
  • Identification, analysis and monitoring of environmental risks.

Oceanography:

  • Ocean, watercourse, and wind monitoring;
  • Wave spectrum for numerical forecast models;
  • Submarine topography mapping (specific conditions);
  • Ocean pollution caused by oil spills and natural slicks;
  • Ship detection - illegal fishing;
  • Support for establishing maritime routes.

Land use :

  • Land use planning;
  • Soil classification;
  • Land use classification;
  • Inventory, change detection, planning;
  • Irrigation patterns/hydrological deficit;
  • Soil salinization.

seta_a3.gif - 268 Bytes Radar Topics


SAR Image Generation

The basic geometry of a Synthetic Aperture Radar imaging system is shown at the figure below. In this system, the platform (aircraft or satellite) with the SAR sensor moves with a velocity V relative to the ground, with an altitude H, pointing the antenna laterally with an angle in relation to nadir.

Figure - SAR system geometry

As the platform moves the transmitter send pulses with lengths Tp in regular intervals of T seconds, as shown in the following figure:

Figure - Transmitted pulse

The transmitted pulse is modulated linearly in frequency (known as chirp), with the frequency varying from a minimum to a maximum value. This variation in frequency is known as pulse bandwidth,, and it determines the resolution in the direction perpendicular to the flight (range).

To better understand what occurs in a SAR imaging system, the behavior of a point target is used, from the time it enters until it departures from the field of view of the antenna.

The figure below shows the imaging of a point P, since its entrance in the antenna field of view, in the instant , until its departure in the instant . In the time interval the radar sends a number N of pulses; in this way, N samples from the echo of the point P are collected in this time interval. These samples are stored in some memory device. During the interval , the SAR platform moves V. meters, which is known as the length of the Synthetic Aperture.

Figure - Interval of the synthetic aperture .

The received echo of a sent pulse suffers a variation in frequency due to the velocity V of the platform. This variation is known as the Doppler effect. The variation of the frequency in the interval to is known as Doppler bandwidth, .

The variations of the frequency and influence directly the range and azimuth resolutions respectively; the higher, the better are the resolutions.

The data (echoes) acquired by a SAR system need to have a processing that will generate an image about these data. In the past, the processing was performed by an optical system, not much flexible, inaccurate and expensive. With the development of faster computers it is possible to generate more precise digital SAR images, through suitable algorithms.

Multi-Look Processing

The multi-look process consists in dividing the synthetic aperture in several looks. The figure below illustrates an example of the division of the synthetic aperture in three looks.

Figure - Example of multi-look, number of looks is 3.

The final image is composed by the average of the images of each look, which are generated separately. It is assumed that the images of each look are statistically independent. This technique increases the signal-to-noise ratio of the final image, proportional to the square root of the number of looks, reducing, then, the effect of the speckle noise.

The multi-look processing causes a degradation in the azimuth resolution, since the images of each look have a bandwidth smaller than the total width, that is:

where "nl" is equal to the number of looks.

 

The azimuth resolution in this case is "nl" times smaller than the one-look image.

 

See also:
Reading Images at SPRING
How to register an image?
Image Processing Techniques.