Why Coherence is not a valid metric when performing impact excitation?
a good reference is:


  Carter GC. Coherence and time delay estimation. Proceedings of the IEEE. 1987 Feb;75(2):236-55


The coherence is actually complex valued and bound by a magnitude of one.  I believe you are referring to the magnitude squared coherence as used in Carter's paper.  The term coherence by itself is used in optics.  

The problem with the MSC is the probability density of the estimate of MSC, it takes a lot of independent samples to get a reasonably accurate estimate. When applied to a single sample, the confidence region is [0 1] at any type two error, which essentially implies that a single sample has to considered a deterministic signal and not the random model.  The following paper covers how to calculate the pdf of the sample MSC. 


  T. Barnard, "Legendre polynomial expressions for the probability
  density function of magnitude-squared coherence estimates," in IEEE
  Transactions on Acoustics, Speech, and Signal Processing, vol. 29, no.
  1, pp. 107-108, February 1981. doi: 10.1109/TASSP.1981.1163516
  Abstract: Carter, Knapp, and Nuttall [1] presented a discrete Fourier
  transform (DFT) method for estimating the magnitude-squared coherence
  between two zero-mean wide-sense-stationary random processes. This
  paper shows that a simple Legendre polynomial expression can replace
  the hypergeometric function used in the probability density function
  expression of Carter et al. [1] (see also Fisher [2] and Goodman [3])
  for the coherence estimate obtained from nonoverlapped DFT's. A
  standard Legendre polynomial recursion provides a recursive method for
  evaluating the density expression. keywords: {Polynomials;Probability
  density function;Density functional theory;Frequency;Discrete Fourier
  transforms;Signal processing algorithms;Random
  processes;Instruments;Detectors;Distributed computing}, URL:
  http://ieeexplore.ieee.org.mutex.gmu.edu/stamp/stamp.jsp?tp=&amp;arnumber=1163516&amp;isnumber=26151


If you have the symbolic toolbox, you can use the following matlab code to calculate the MSC pdf using the expression from the Carter paper.

clear all
%nd=128
n=[ 1 32 512 768 ]
c=linspace(0,1,512);
p=zeros(length(n),length(c));
for k=1:length(n)
nd=n(k)
%syms  C Ch
C=.5;
p(k,:)=Magsquarecoherepdf(c,C,nd);
end
figure(1)
plot(c,p,'Linewidth',2)
h1=legend('1', '32','512', '768');
title(h1,'Number Trials');
title(['Sample Density given $\mid \gamma \mid^2 = $',num2str(C)],'FontWeight','bold','Interpreter','latex')
h=xlabel('Sample $\mid \tilde{\gamma} \mid^2$','FontWeight','bold','Interpreter','latex');

function [p]=Magsquarecoherepdf(c,C,nd)
%
p=zeros(size(c));
for i=1:length(c)
Ch=c(i);
t1=log10(hypergeom([1-nd 1-nd],1 , Ch*C));
assert(~isnan(t1),'t1 nan')
t2=log10((nd-1).*((1-Ch.*C)./(1-C).^2));
assert(~isnan(t2),'t2 nan');
t3=log10(((1-C).*(1-Ch)./(1-Ch.*C).^2))*nd;
assert(~isnan(t3),'t3 nan');
p(i)=10.^(t1+t2+t3);
%assert(~isnan(p(i)),['p  assert ',num2str(t1),' ', num2str(t2),' ', num2str(t3)])
end
return


If you repeat your impacts, you have an ensemble and I believe you could apply the MSC to your problem.

edit:

If you might permit an analogy. lets say you are asked to determine if a coin is fair in a toss. You can't say very much from a single flip of a coin. you have to repeat the toss , and keep on repeat tossing it. the number  of tosses required for a specific accuracy is determined from a probability law. a single toss tells you nothing. 

the same is true for the MSC. a single trial says nothing. it needs to be repeated and the probability density in the code above specifies the number of trials required for  a specified accuracy