In[1]:= ARProcess[{Array[a, {2, 2}]}, Array[v, {2, 2}]]
Out[1]= ARProcess[{{{a[1, 1], a[1, 2]}, {a[2, 1], a[2, 2]}}}, {{v[1, 1], v[1, 2]}, {v[2, 1], v[2, 2]}}]
denotes AR process of order p=1, dimension 2. The coefficients of a vector process are defined to be square matrices n by n, where n is the dimension of the process. So to define 2-dimensional AR process of order say p=4 with symbolic coefficients using Array one does:
In[2]:= ARProcess[{Array[a, {4, 2, 2}]}, Array[v, {2, 2}]]
Out[2]= ARProcess[{{{{a[1, 1, 1], a[1, 1, 2]}, {a[1, 2, 1],
a[1, 2, 2]}}, {{a[2, 1, 1], a[2, 1, 2]}, {a[2, 2, 1],
a[2, 2, 2]}}, {{a[3, 1, 1], a[3, 1, 2]}, {a[3, 2, 1],
a[3, 2, 2]}}, {{a[4, 1, 1], a[4, 1, 2]}, {a[4, 2, 1],
a[4, 2, 2]}}}}, {{v[1, 1], v[1, 2]}, {v[2, 1], v[2, 2]}}]
One could also use different names for each coefficient matrix:
In[3]:= ARProcess[{Array[a, {3, 3}], Array[b, {3, 3}]}, Array[v, {3, 3}]]
Out[3]= ARProcess[{{{a[1, 1], a[1, 2], a[1, 3]}, {a[2, 1], a[2, 2],
a[2, 3]}, {a[3, 1], a[3, 2], a[3, 3]}}, {{b[1, 1], b[1, 2],
b[1, 3]}, {b[2, 1], b[2, 2], b[2, 3]}, {b[3, 1], b[3, 2],
b[3, 3]}}}, {{v[1, 1], v[1, 2], v[1, 3]}, {v[2, 1], v[2, 2],
v[2, 3]}, {v[3, 1], v[3, 2], v[3, 3]}}]
which defines AR process of order 2 and dimension 3, with coefficient matrices a and b, and noise covariance matrix v.
This may also be helpful:
ARProcess reference page