interpolate data in timeseries

v=[0.18  3.15  0.18  0.16  0.17 0.58 0.33 ];                    % example data
% the engine
nI=3;                                                           % number points to insert
N=numel(v);                                                     % initial vector size
NN=(N-1)*nI+N;                                                  % new N for augmented v
xv=linspace(1,N,NN);                                            % uniform spacing along 1:N NN points
vv=interp1(1:N,v,xv);                                           % linear interpolation
vvv=interp1(1:N,v,xv,'pchip');                                  % or pchip interpolation

Illustrate results...

plot(v,'o-')
hold on
plot(xv,vv,'x')
plot(xv,vvv,'d-')
legend('Original','Linear','PChip')

produces

"Choose your poison" as far as what interpolant you actually want.

If you have Signal Processing TB, there's also resample you could play with.