  We apply the $l_1$ minimizing technique of compressive sensing (CS) to
non-linear quadratic observations. For the example of coherent X-ray scattering
we provide the formulae for a Kalman filter approach to quadratic CS and show
how to reconstruct the scattering data from their spatial intensity
distribution.
