Besides spatial resolution, the peak sidelobe ratio (<i>PSLR</i>) 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 σ<sup>0</sup> as small as possible in order to limit the backscattered clutter energy. For SAR systems with low <i>PSLR</i> requirements the effect of this clutter is mostly neglected and the <i>PSLR</i> 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 <i>PSLR</i> 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 <i>PSLR</i> 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 <i>PSLR</i>. This approach exploits the statistical properties of mainlobe and sidelobe with consideration of point target and clutter energy. Error bounds of the estimated <i>PSLR</i> are derived using established parameters such as signal-to-clutter ratio (<i>SCR</i>) and the classically defined <i>PSLR</i>. Furthermore some simulational results are presented which enable an evaluation of the calculated error bounds.