  Estimating the number of sources received by an antenna array have been well
known and investigated since the starting of array signal processing. Accurate
estimation of such parameter is critical in many applications that involve
prior knowledge of the number of received signals. Information theo- retic
approaches such as Akaikes information criterion (AIC) and minimum description
length (MDL) have been used extensively even though they are complex and show
bad performance at some stages. In this paper, a new algorithm for estimating
the number of sources is presented. This algorithm exploits the estimated
eigenvalues of the auto correlation coefficient matrix rather than the auto
covariance matrix, which is conventionally used, to estimate the number of
sources. We propose to use either of a two simply estimated decision
statistics, which are the moving increment and moving standard deviation as
metric to estimate the number of sources. Then process a simple calculation of
the increment or standard deviation of eigenvalues to find the number of
sources at the location of the maximum value. Results showed that our proposed
algorithms have a better performance in comparison to the popular and more
computationally expensive AIC and MDL at low SNR values and low number of
collected samples.
