Dual-frequency multi-polarization Spaceborne Synthesis Aperture Radar (SAR) can obtain multi-polarization images of large ground area synchronously. These images include multiple information of the ground target. It benefits target detection, identification, and classification. For high-orbit multi-polarization Spaceborne SAR, it’s difficult to solve the problem of range ambiguity when the look angle is variable. In this paper, ambiguity property of multi-polarization Spaceborne SAR system is analyzed. And Polarization Time Division (PTD), Polarization Frequency Division (PFD), and Polarization Code Division (PCD) characteristics of multi-polarization Spaceborne SAR system are compared in detail. Ground experiment system of Dual-frequency multi-polarization Spaceborne SAR and its performance are presented.
Pulse Repeat Frequency (PRF) is a very important parameter in the Synthetic Aperture Radar (SAR) system. It affects other parameters and determines the radar performance. For a conventional procedure to select PRF for SAR, the earth is treated as a ball, and the orbit as a circle. At this time, the error from the calculating distance between the satellite and the target on the earth surface must exist. It severely affects the right selection of PRF. To avoid this error, in this paper, the model for the earth is an ellipsoid and the orbit is an ellipse. And it is specified a space coordinate, in which the error for the distance between the satellite and targets is corrected and the PRF selection for SAR is discussed. Finally the approach is used to derive an available PRF plot and the azimuth/range ambiguity to signal ratio. As comparison, the same results in circle orbit and round earth are specified.
The conventional filters can't achieve good effects in reducing speckle for high resolution single-look spaceborne synthetic aperture radar(SAR) images. In this paper an algorithm on efficiently reducing speckle is developed. This algorithm uses multiple structuring elements to replace common structuring elements so as to create an omni-directional multiple structuring elements soft-morphological filter whose weight values can be obtained through the improved impulse Bp neural network(NN) self-adaptive method. The performance of this algorithm is analyzed in detail. Finally, the raw data of RADARSAT is used to demonstrate its efficiency. The result shows that the filter can bring better effect than other filters.
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