Radar Post-Processing

  • Daniel R. Nüesch
  • Erich H. Meier
Conference paper
Part of the Ispra Courses book series (ISPA)


The major goal of this chapter is to discuss various problems involved in radar image analysis. Although the information contained in analogue radar imagery will satisfy the needs of a majority of users, more sophisticated analysis of the data may be required for specific tasks. Without going deeply into the mathematics, this chapter covers two areas of radar image processing: geometric rectification for co-registering the image to a map in order to locate the position of a feature in an absolute sense, and digital image processing techniques to support the information extraction procedure.

After the SAR image formation process, also called “image correlation”, the radar data are in a two-dimensional image format, such as a regular photograph or an image stored on magnetic tape. However, a number of processing steps are still required to make the images more easily interpretable for specific applications. For example, the use of high or low contrast paper and the over and underexposing of film are two techniques which may be used to highlight certain features. Similarly, numerous techniques can be used to enhance digital remotely sensed data on high speed computers. In this chapter we will discuss procedures which are used to achieve radiometric and geometric calibration. Radiometric calibration involves corrections for antenna pattern shading and other nonlinear processes in the sensor or the correlator, in order to relate the intensity of each pixel to the surface backscatter cross section directly. The geometric correction also serves the same purpose in the sense that it involves the adjustment of the precise spatial location of each pixel in the image such that it could be superimposed on a well-defined cartographic reference.


Pulse Transit Time Radar Beam Grey Tone Azimuth Direction Slant Range 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© ECSC, EEC, EAEC, Brussels and Luxembourg 1989

Authors and Affiliations

  • Daniel R. Nüesch
    • 1
  • Erich H. Meier
    • 1
  1. 1.Remote Sensing LaboratoriesUniversity of ZürichSwitzerland

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