  Direction of Arrival (DOA) estimation of mixed uncorrelated and coherent
sources is a long existing challenge in array signal processing. Application of
compressive sensing to array signal processing has opened up an exciting class
of algorithms. The authors investigated the application of orthogonal matching
pursuit (OMP) for direction of Arrival (DOA) estimation for different
scenarios, especially to tackle the case of coherent sources and observed
inconsistencies in the results. In this paper, a modified OMP algorithm is
proposed to overcome these deficiencies by exploiting maximum variance based
criterion using only one snapshot. This criterion relaxes the imposed
restricted isometry property (RIP) on the measurement matrix to obtain the
sources and hence, reduces the sparsity of the input vector to the local OMP
algorithm. Moreover, it also tackles sources irrespective of their coherency.
The condition for the weak-1 RIP on decreased sparsity is derived and it is
shown that how the algorithm gives better result than the OMP algorithm. With
an addition to this, a simple method is also presented to calculate source
distance from the reference point in a uniform linear sensor array. Numerical
analysis demonstrates the effectiveness of the proposed algorithm.
