Estimation of real-valued sinusoidal signal frequencies based on ESPRIT and propagator methods

In this paper, two new techniques are proposed for estimating multiple real-valued sine wave frequencies based on ESPRIT and propagator methods. These techniques are direct methods, which do not require any peak search. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. Then, the ESPRIT and propagator based techniques are presented using the proposed new data model. The frequency estimation technique based on propagator is a computationally efficient method which does not require eigen decomposition of the covariance matrix of the observation as like ESPRIT based method. So it requires less computational complexity as compare to ESPRIT based technique at the cost of negligible deviation in the estimate. Computer simulations are carried out to demonstrate the performance of the proposed techniques.