It is well know that $SO(3)$ is defined as: $$O(3)=\big\{\psi\in GL(3,\mathbb R):\psi^t\circ\psi=id\big\}$$ What is the geometric idea behind $\psi\circ\psi^t=id$?
Maybe, if we impose that a linear map $\psi:\mathbb R^3\to \mathbb R^3$ is bijective and has a one fixed point, could we deduce that $\psi^t\circ\psi=id$?
The idea is that the orthogonal matrices preserve distance and angle. The dot product (scalar product) give us distances and angles.
For example: $\langle \bf v, \bf v \rangle = \| \bf v \|^2$ where $\langle \bf v, \bf v\rangle$ is the dot product (scalar product) of $\bf v$ with $\bf v$, and $\| \bf v \|$ is the length of $\bf v$. While $\langle \bf v, \bf w \rangle = \|\bf v\|\|\bf w\|\cos\theta$, where $\theta$ is the included angle between $\bf v$ and $\bf w$.
Given a column vectors
$${\bf v} = \left(\begin{array}{c} 1 \\ 2 \\ 3\end{array}\right) \ \ \ \ \ {\bf w} = \left(\begin{array}{c} 2 \\ 5 \\ 9\end{array}\right)$$
We can find the dot product (scalar product) by matrix multiplication: $\langle \bf v, \bf w \rangle = {\bf v}^{\top}{\bf w}$ $$\left(\begin{array}{ccc} 1 & 2 & 3 \end{array}\right)\left(\begin{array}{c} 2 \\ 5 \\ 9\end{array}\right) = 1\times 2+2\times 5+3\times 9 = 39$$
The dot product (scalar product) can be given by $\langle \bf v, \bf w \rangle = \bf v^{\top}\bf w$.
Now let's say we perform a linear transformation. Let $M$ be the matrix transformation. We have $\bf v$ sent to $M\bf v$ and $\bf w$ set to $M\bf w$.
What happens to the angles and the distances? What happens to $\langle \bf v, \bf w \rangle$? Well $$\langle {\bf v}, {\bf w} \rangle \longmapsto \langle M{\bf v}, M\bf w \rangle$$
Using matrix multiplication we have \begin{eqnarray*} \langle M{\bf v}, M\bf w \rangle &=& (M{\bf v})^{\top}(M{\bf w}) \\ &=& {\bf v}^{\top}M^{\top}M{\bf w} \end{eqnarray*}
The dot product (scalar product), which measures angles and distances, is preserved if, and only if, \begin{eqnarray*} \langle {\bf v}, {\bf w}\rangle &=& \langle M{\bf v}, M{\bf w}\rangle \\ \\ {\bf v}^{\top}{\bf w} &=& ({M\bf v})^{\top}{M \bf w} \\ \\ {\bf v}^{\top}{\bf w} &=& {\bf v}^{\top}M^{\top}M{\bf w} \\ \\ {\bf v}^{\top}{\bf w} &=& {\bf v}^{\top}(M^{\top}M){\bf w} \end{eqnarray*} This means that angles and distances are preserved by a linear transformation, with matrix representation $M$, if and only if, $M^{\top}M = E$, where $E$ is the identity matrix.
Notice that $M^{\top}M = E \implies \det(M^{\top}M) = \det(E) \implies \det(M)^2 = 1$. This means that $\det(M) = \pm 1$ and so all orthogonal matrices have determinant $-1$ or $+1$. The special orthogonal matrices, $\mathrm{SO}(n)$, have positive determinant and preserve orientation.