Radiometric Performance of Beamforming in Multistatic SAR Correlation Tomography

This letter investigates the radiometric performance of Beamforming in Correlation Tomography, a Tomographic synthetic aperture radar (TomoSAR) processing technique that exploits pairs of simultaneous acquisitions to provide 3-D reconstructions robust to temporal decorrelation. This advantage makes it particularly suitable for monitoring natural targets, where satellite revisit times of days or weeks would otherwise severely degrade conventional TomoSAR performance. The unique structure of the resulting SCM introduces distinct patterns in the variance of the vertical backscattered power profile. We derive a closed-form expression for the variance of the beamformer power estimate; this analytical framework can use any scene covariance model as input, moreover, we show that under realistic decorrelation assumptions (i.e., complete decorrelation between passes), the variance can be approximated as a function of system parameters alone. Validated against simulated bistatic TomoSAR responses under diverse configuration and scene structures, we establish this framework value as a mission design tool by providing an application example, directly mapping key system requirements, such as the number of passes, looks, and SNR to final biophysical product quality, specifically Above Ground Biomass density (AGBd) estimation precision.