Your system of equations can be represented in matrix form as
\dot{X} = AX
The usual technique involves finding a diagonal matrix D, such that D = P^(-1)AP, and where the columns of P are the eigenvectors of A, and the entries on the diagonal of D are the eigenvalues of A. The process of diagonalization to solve a system of linear DEs is too involved for me to describe it all right here, but presumably you have seen it discussed in your class.
One thing to note about the matrix that comes out of your system of equations: the matrix A of coefficients of x_1 and x_2 causes a rotation by an angle -t. An eigenvector of a matrix A is a vector x such that Ax = \lambdax. In other words, multiplying an eigenvector x produces another vector that is merely a scalar multiple of x. Due to the fact that your matrix A is a rotation matrix, I don't see how Ax can produce a vector that is a scalar multiple of x, for arbitrary rotation angles t.