Persistent scatterer selection using maximum likelihood estimation

We present here a new InSAR persistent scatterer selection method using maximum likelihood estimation to identify persistent scattering pixels, which results in a denser network of reliable phase measurements than do existing methods. We analyze the phase of each pixel in a series of interferograms and estimate the relative strength of any slowly fluctuating component of the radar echo from a dominant scatterer to the background scattering within a pixel. We find a fairly dense network of scatterers with stable phase characteristics in areas where conventional InSAR fails due to decorrelation. We examined data over two vegetated regions in the San Francisco Bay Area. The average phases of these pixels clearly show the slip along the Hayward fault, and set upper bounds on any slip along the Bay Area segment of the San Andreas fault.