
Thu May 20, 2010 4:51 am
notation:
i=(1,0,0)
j=(0,1,0)
k=(0,0,1)
I=3x3 identity matrix
M(trans)=the transpose of the matrix M
*=matrix multiplication
i'=M*i=the image of i
j'=M*j=the image of j
k'=M*k=the image of k
(dot)=the dot product
0=0
M1c=the vector formed by the first column of M
M2c=the vector formed by the 2nd column of M
M3c=the vector formed by the 3rd column of M
We must first realize that the nth column of any matrix (not just orthogonal ones) is just the image of the nth basis vector under matrix multiplication. To see this, just take any random 3x3 matrix and try M*i, M*j, and M*k. You'll just get the columns of the original matrix. Using my above notation:
M1c=M*i=i'
M2c=M*j=j'
M3c=M*k=k'
Okay, with that understood, this becomes easy. If your definition of orthogonal matrix is that M*M(trans)=I, then consider:
Getting the elements of I is the same as (dot)ing a column of M with a row of M(trans), but rows of M(trans) are columns of M. So the ones along the diagonal of I are telling you that:
M1c(dot)M1c=1
M2c(dot)M2c=1
M3c(dot)M3c=1
which we can reinterpret as:
i'(dot)i'=1
j'(dot)j'=1
k'(dot)k'=1
which means these images are all of length 1
Similarly, all the 0's in I are just telling us, multiple times over, that:
i'(dot)j'=0
i'(dot)k'=0
j'(dot)k'=0
which is what it means (algebraically) for these various images to be orthogonal to each other.
And so we can see that M*M(trans)=I is nothing more than a nice compact algebraic way of saying that M transforms the standard orthonormal basis into another one.
I am Srime