How can I estimate Kalman Filter with log-likelihood function?

Hi, I have to estimate the following Kalman Filter using a maximum likelihood approach. x(t+1) = A*x(t) + w(t), w ~ N(0, Q), x(0) ~ N(init_x, init_V) y(t) = C*x(t) + v(t), v ~ N(0, R)

where A is a (1x2) vector and x(t) is a (2x1) vector I have y(t) and I need to estimate x(t), A, C, Q, R

how do I write my log-likelihood function so that it finds the parameters which maximize the function?

thank you