How to find an Orthonormal Basis for Null( A$^T$ )

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I'm studying for an exam and I'm not sure how to do this. I understand what the definitions mean (for the most part) but I'm not sure how to apply it to the problem.

Let

A = \begin{pmatrix}1/2&-1/2\\1/2&-1/2\\1/2&1/2\\1/2&1/2 \end{pmatrix}

a) Find an orthonormal basis for Null( A$^T$ )

and

b) Determine the projection matrix Q that projects vectors in $\mathbb{R}$$^4$ onto Null(A$^T$).

My thoughts:

The matrix's column vectors are definitely orthonormal, so I want to find a basis such that for any x, Ax = 0.

For b) I want to use the projection formula and find some vector b within the above basis?

Help / an explanation of steps would be appreciated, thanks.

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Solution To Part (a)
I’ll go through the general method, although in this case you can almost eyeball the solution.

One way to find a basis for the kernel (a.k.a. nullspace) of a matrix is to use row-reduction. Row-reducing $A^T$ goes pretty quickly since there are only two rows, producing $$ R=\pmatrix{1&1&0&0\\0&0&1&1} $$ Find the columns that don’t have leading entries, in this case, the second and last. Basis vectors for the kernel will have a one on one of the rows that corresponds to these positions and zeroes in the others, so we’ll have $\langle a,1,b,0\rangle$ and $\langle c,0,d,1\rangle$ as our basis vectors. Formally, you’d now solve for the missing components, but in practice you can just read them from the row-reduced matrix:$$ R\pmatrix{a\\1\\b\\0}=\pmatrix{a+1\\b}=0, $$ so $a=-1$ and $b=0$. But these values are just the second column of $R$ negated. Similarly, the second basis vector will be $\langle0,0,-1,1\rangle$. These vectors are obviously orthogonal, so all you need to do is normalize them, yielding $$ \pmatrix{-\frac1{\sqrt2}\\\frac1{\sqrt2}\\0\\0}\text{ and }\pmatrix{0\\0\\-\frac1{\sqrt2}\\\frac1{\sqrt2}}. $$

Hint For Part (b)
Use the fact that projection onto $\operatorname{ker}A^T$ can be broken down into projections onto its basis vectors.