In the book "The mathematics of computerized tomography" by Natterer comes the theorem:
Theorem 1.1 $f=A^+g$ is the unique solution of $A^*Af=A^*g$ in $range(A^*)$.
where $A:H\rightarrow K$ is a linear bounded operator, $H$ and $K$ are Hilbert spaces, $g\in range(A)\oplus range(A)^\perp$ and $f=A^+g$ is the minimizer of $\| Af-g\|_K$. Here is supposed that the adjoint exists.
Now I copy exactly the proof in the book:
$f$ minimizes $\|Af-g\|$ if and only if $(Af-g,Au)=0$ for all $u\in H$, i.e., if and only if $A^*Af=A^*g$. Among all solutions of this equation the unique element with least norm is the one in $(ker(A))^\perp=\overline{range(A^*)}$.
My concern: I haven't been able to prove that this solution $f\in \ker(A)^\perp$ and is unique. I know $g=Af+v$ where $v\in range(A)^\perp=\ker(A^*)$ but I cant find a way to relate it with $(f,u)=0$ for all $u\in\ker(A)$ because I dont know how to introduce $A$ in this equation. Any suggestion is valuable.