PSLR estimation for SAR systems with consideration of clutter background

Klemens Letsch; Patrick Berens

doi:10.1117/12.627589

12 October 2005 PSLR estimation for SAR systems with consideration of clutter background

Klemens Letsch, Patrick Berens

Proceedings Volume 5980, SAR Image Analysis, Modeling, and Techniques VII; 598002 (2005) https://doi.org/10.1117/12.627589
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

Abstract

Besides spatial resolution, the peak sidelobe ratio (PSLR) is another important parameter to assess the quality of a SAR system. For the verification of SAR performance parameters, usually the point target responses of a number of ground-fixed reference targets such as corner reflectors or active transponders are evaluated in the processed SAR image. The area around these reference targets should consist of a (natural) cover with a radar backscattering coefficient σ⁰ as small as possible in order to limit the backscattered clutter energy. For SAR systems with low PSLR requirements the effect of this clutter is mostly neglected and the PSLR is determined in a classical manner by the estimation of mainlobe and sidelobe amplitudes from the range and azimuth section of the two-dimenensional point target response. The verification of high performance SAR systems, where challenging performance specifications are to be fulfilled, requires a more accurate PSLR estimation. Hence, the ground clutter of the surrounding target area has to be taken into account. Due to the ground clutter's statistical nature the superposition of the clutter with mainlobe/sidelobe amplitude is stochastic, therefore these amplitudes and the PSLR itself can be regarded as random variables. In our paper we suggest a combined deterministic-statistical approach as a tradeoff to the fully statistical modelling of the PSLR. This approach exploits the statistical properties of mainlobe and sidelobe with consideration of point target and clutter energy. Error bounds of the estimated PSLR are derived using established parameters such as signal-to-clutter ratio (SCR) and the classically defined PSLR. Furthermore some simulational results are presented which enable an evaluation of the calculated error bounds.

Citation Download Citation

Klemens Letsch and Patrick Berens "PSLR estimation for SAR systems with consideration of clutter background", Proc. SPIE 5980, SAR Image Analysis, Modeling, and Techniques VII, 598002 (12 October 2005); https://doi.org/10.1117/12.627589

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