Computation of Weight Function of 2qth Order Virtual Array to Analyse the Estimation Performance

To estimate the large number of sources using an
array of lesser number of sensors is an important problem
and of interest to many researchers. This problem has also
been tackled with the virtual array based approach where the
covariance and cumulant lags provide a virtual sensor. Here,
an important parameter which affects the parameter estimation
accuracy and latency is weight function. The weight function is
defined as the frequency of occurrence of each virtual sensor in
the virtual array. We provide the close-form expression of higher
order virtual array corresponding to linear array. Afterwards, we have analytically evaluated the weight function of virtual
array and study the effect of the weight function on parameter
estimation. Simulation results show the parameter estimation
accuracy is significantly improve with high weight function.