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In this paper, we investigate the direction of arrival (DOA) estimation problem of noncircular signals for coprime linear array (CLA). From the perspective of the CLA as extracted from a filled uniform linear array (ULA), a noncircular root-MUSIC algorithm is proposed to estimate the DOA which can avoid the spectral peak search and lower the computational complexity. Due to the noncircular characteristic, the proposed algorithm enables to resolve more sources than sensors. Meanwhile, the proposed algorithm has better angle estimation performance than some conventional DOA estimation algorithms. Numerical simulation results illustrate the performance of the proposed method.

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

A new method based on the fractional Fourier domain signal subspace decomposition for DOA estimation of wideband LFM sources in sensor arrays is introduced. The proposed approach detects LFM sources with fractional Fourier transform (FRFT), estimates their parameters, and constructs the fractional Fourier domain correlation matrix of the sensor array signals as well as the steering vector corresponding to each source. The MUSIC algorithm is then used to estimate the DOA of LFM sources. Its performance is numerically evaluated.

The issue of direction of arrival (DOA) estimation for co-prime MIMO radar is studied, and an estimation method based on unitary root-MUSIC is proposed. The co-prime MIMO radar has M-element transmit array and N-element receive array with Nλ/2 and Mλ/2 being the inter-element distances, respectively (λ means the wavelength, and M and N are co-prime integers). The algorithm firstly utilizes unitary transformation to transform the complex eigenvalue decomposition (EVD) into real-valued one, which can reduce the complexity. Thereafter, as the virtual elements generated by co-prime MIMO radar are not continuous, the sorting and zero filling operations are carried out to establish a standard polynomial root finding form. Finally, the DOA can be estimated by finding the roots of the polynomials. Due to the using of co-prime array for MIMO radar, the proposed algorithm can achieve much better DOA estimation performance and determine more targets than conventional methods using compact arrays.

Spatial stepped-frequency multiple input multiple output (MIMO) array model is proposed to improve the resolution of MIMO radar. Two-sided correlation transformation (TCT) focusing algorithm and iterative power spectrum reconstruction (IPSR) algorithm are extended to this situation. TCT focusing algorithm estimates the direction of arrival (DOA) in reference frequency after focusing the signals of different frequency to the reference frequency, while IPSR estimates the DOA by reconstructing the power spectrum of different frequency signals iteratively. Simulation results show that the performance of IPSR algorithm is better than that of TCT focusing algorithm.

In order to estimate the spatial orientation of weak signal accurately, DOA estimation algorithm for coherent weak target signal in strong interference environment was proposed. Firstly, this algorithm carried out the decorrelation of the coherent weak signal via modified Toeplitz matrix. Then, the strong interference signal corresponding to the feature vector was removed from the subspace. Finally, DOA estimation of the weak signal was accomplished by making use of MUSIC algorithm. Simulation results indicate that the algorithm can eliminate the influence of strong interference signal effectively.