An Improved Wideband Covariance Matrix Sparse Representation (W-CMSR) Method for Wideband Direction of Arrival Estimation Using Simulated Annealing
نویسنده
چکیده
In this paper, we optimize the size of aperture and number of sensors for Wideband Covariance Matrix Sparse representation (W-CMSR) method for Wideband Direction of Arrival estimation using Simulated Annealing. The performance of W-CMSR is obtained with initial number of sensors and aperture size. Then, we find the performance of W-CMSR with optimized number of sensors and aperture size using simulated annealing. We observe that same performance of WCMSR is obtained with reduced number of sensors and aperture size by using simulated annealing.
منابع مشابه
Covariance-Based Direction-of-Arrival Estimation of Wideband Coherent Chirp Signals via Sparse Representation
This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during...
متن کاملDOA estimation of wideband signals based on slice-sparse representation
In this article, the direction-of-arrival (DOA) estimation problem of wideband signal sources is studied. We pass the incident signals through a bank of narrowband filters to split the array outputs into several narrowband components. Then, a novel slice-sparse representation model of the joint narrowband array covariance data is proposed in the frequency domain to enforce joint sparsity in the...
متن کاملSparse representation-based DOA estimation of coherent wideband LFM signals in FRFT domain
In this paper, the method of direction-of-arrival (DOA) estimation for wideband signals based on sparse representation of FRFT domain is proposed by using the excellent convergence of FRFT to LFM signals. This method focuses the wideband signal to the reference frequency using FRFT, establishes the DOA estimation model and the array manifold matrix in the FRFT domain, and reconstructs the spati...
متن کاملWideband DOA Estimation via Sparse Bayesian Learning over a Khatri-Rao Dictionary
This paper deals with the wideband directionof-arrival (DOA) estimation by exploiting the multiple measurement vectors (MMV) based sparse Bayesian learning (SBL) framework. First, the array covariance matrices at different frequency bins are focused to the reference frequency by the conventional focusing technique and then transformed into the vector form. Then a matrix called the Khatri-Rao di...
متن کاملUnderdetermined Wideband DOA Estimation for Off-Grid Sources with Coprime Array Using Sparse Bayesian Learning
Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to resolve more sources than the number of physical sensors. The sparse-based DOA estimation can deteriorate the detection and estimation performance be...
متن کامل