Define $\left[\frac{1}{|x|^d}\right]$ on $\mathbb{R}^d$ as $$\left[\frac{1}{|x|^d}\right](\varphi) = \int_{|x|\le 1}\frac{\varphi(x)-\varphi(0)}{|x|^d} dx + \int_{|x| > 1}\frac{\varphi(x)}{|x|^d} dx.$$
It is easy to show that $\left[\frac{1}{|x|^d}\right]$ is a tempered distribution. It also agrees with $1/|x|^d$ away from the origin.
According to my textbook, the Fourier transform of the distribution $\left[\frac{1}{|x|^d}\right]$ equals $c_1 \log |\xi| + c_2$, with $c_1 \neq 0$.
However, I don't see how to prove this claim. Below is how far I've got, with $F$ standing for $\left[\frac{1}{|x|^d}\right]$.
\begin{align} \hat{F}(\varphi) &= F(\hat{\varphi}) = \int_{|x|\le 1}\frac{\hat{\varphi}(x)-\hat{\varphi}(0)}{|x|^d} dx + \int_{|x| > 1}\frac{\hat{\varphi}(x)}{|x|^d} dx \\&= \int_{\mathbb{R}^d} \left(\int_{|x|\le 1}\frac{\varphi(\xi)(e^{-2\pi i \xi \cdot x}-1)}{|x|^d} dx + \int_{|x| > 1}\frac{\varphi(\xi)e^{-2\pi i \xi \cdot x}}{|x|^d} dx\right) d\xi \\&= \int_{\mathbb{R}^d} \varphi(\xi) \left(\int_{|x|\le 1}\frac{(e^{-2\pi i \xi \cdot x}-1)}{|x|^d} dx + \int_{|x| > 1}\frac{e^{-2\pi i \xi \cdot x}}{|x|^d} dx\right) d\xi. \end{align}
So it is left to prove that $$\int_{|x|\le 1}\frac{(e^{-2\pi i \xi \cdot x}-1)}{|x|^d} dx + \int_{|x| > 1}\frac{e^{-2\pi i \xi \cdot x}}{|x|^d} dx = c_1 \log|\xi|+c_2.$$