Guangmin Wang

Computationally Efficient Subspace-Based Method for Two-Dimensional Direction Estimation With L-Shaped Array

In order to mitigate the effect of additive noises and reduce the computational burden, we propose a new computationally efficient cross-correlation based two-dimensional (2-D) direction-of-arrivals (DOAs) estimation (CODE) method for noncoherent narrowband signals impinging on the L-shaped sensor array structured by two uniform linear arrays (ULAs). By estimating the azimuth and elevation angles independently with a one-dimensional (1-D) subspace-based estimation technique without eigendecomposition, where the null spaces are obtained through a linear operation of the matrices formed from the cross-correlation matrix between the received data of two ULAs, then the pair-matching of estimated azimuth and elevation angles is accomplished by searching the minimums of a cost function of the azimuth and elevation angles, where the computationally intensive and time-consuming eigendecomposition process is avoided. Further the asymptotic mean-square-error (MSE) expressions of the azimuth and elevation estimates are derived. The effectiveness of proposed method and the theoretical analysis are verified through numerical examples, and it is shown that the proposed CODE method performs well at low signal-to-noise ratio (SNR) and with a small number of snapshots.

Subspace-based two-dimensional direction estimation and tracking of multiple targets

This paper deals with the problem of tracking the two-dimensional (2-D) direction-of-arrivals (DOAs) of multiple moving targets with crossover points on their trajectories, and we propose a new computationally efficient cross-correlation based 2-D DOA estimation with automatic pair-matching (CODEC) method for noncoherent narrowband signals impinging on the L-shaped sensor array structured by two uniform linear arrays (ULAs) with omnidirectional sensors. The effectiveness of the proposed method and the theoretical analysis are substantiated through numerical examples.

Two-dimensional direction estimation of coherent signals with two parallel uniform linear arrays

In this paper, the problem of estimating two-dimensional (2D) direction-of-arrivals (DOAs) of coherent signals is investigated, and a new computationally efficient subspace-based method is proposed for the multiple coherent narrowband signals impinging on a planar sensor array formed by two uniform linear arrays (ULAs), where the array geometry and shift invariance property of the ULA are exploited to decorrelate the coherency of incident signals, and the cross-correlations between two ULAs are used to mitigate the effect of additive noise in null space estimation, while the pair-matching of the estimated azimuth and elevation angles and computationally burdensome eigendecomposition are avoided. The asymptotic mean-square-error (MSE) expressions of the estimated azimuth and elevation angles are derived explicitly. The effectiveness of the proposed method and the theoretical analysis are substantiated through numerical examples.

Computationally efficient method for joint azimuth-elevation direction estimation with L-shaped array

For overcoming the problems of pairing failure and estimation failure, which are frequently encountered in two-dimensional (2-D) direction-of-arrival (DOA) estimation of multiple signals, we propose a new computationally efficient subspace-based based 2-D DOA estimation with automatic pair-matching method for noncoherent narrowband signals impinging on the L-shaped sensor array structured by two uniform linear arrays (ULAs). In the proposed method the computationally expensive procedures of eigendecomposition in subspace estimation and pair-matching of the estimated azimuth and elevation angles are avoided, while the problems of pairing failure and estimation failure are overcome. The statistical analysis is studied, and the closed-form expressions of the asymptotic mean-square-errors (MSEs) of the elevation and azimuth estimates are derived explicitly. Finally the effectiveness of the proposed method and the theoretical analysis are substantiated through numerical examples.

Direction estimation of uncorrelated and coherent narrowband signals with uniform linear array

In this paper, an effective direction-of-arrival (DOA) estimation method is proposed with a uniform linear array (ULA) when uncorrelated and coherent signals coexist. The direction-of-arrivals (DOAs) of uncorrelated signals and coherent signals are estimated in two steps. The DOAs of uncorrelated signals are estimated using conventional subspace method firstly, then the information of the uncorrelated signals can be eliminated by using matrix difference technique, and finally the coherent signals are decorrelated to be estimated. The theoretical analysis and simulation results show that the proposed method is effective.

New method for joint elevation and azimuth direction estimation with L-shaped array

This paper addresses the problem of estimating the two-dimensional direction-of-arrival (2D DOA) of multiple narrowband signals impinging on an L-shaped array, which is structured by two uniform linear arrays (ULAs). A computationally efficient method without eigendecomposition is proposed, where the elevation angles are estimated from the cross-correlation matrices between the received data of two ULAs by linear operation, then the estimated elevation angles are used to obtain the azimuth angles by another linear operation, thus the pair-matching of estimated azimuth and elevation angles is avoid. Further the asymptotic mean-square-error (MSE) expressions of the estimation errors are derived, and the effectiveness of proposed method and the theoretical analysis are verified through numerical examples.

Two-dimentional direction-of-arrival estimation of coherent signals with L-sharped array

In this paper, a new method is proposed for two-dimensional (2-D) direction-of-arrivals (DOAs) estimation of multiple narrowband coherent signals impinging on an L-shaped sensor arrays structured by two uniform linear arrays (ULAs). The coherency of incident signals is decorrelated through subarray averaging technique, and the null space is obtained through linear operator of the cross-correlation matrix between the received data of two ULAs without eigendecomposition. The elevation angles and the quasi-azimuth angles are firstly decoupled and estimated, and the pair-matching of two groups of angles can be accomplished by using a novel method. Then by investigating the geometrical relationship, the azimuth angles can be obtained. Furthermore the asymptotic mean-square-error (MSE) of the estimated elevation and azimuth angles are derived, and the effectively of the proposed method is verified through numerical examples.

Computationally efficient method for 2-D DOA estimation with L-shaped sensor array

This paper proposes a new computationally efficient method for two-dimensional (2-D) direction-of-arrivals (DOAs) estimation of multiple correlated narrowband signals impinging on an L-shaped sensor array structured by two uniform linear arrays (ULAs). In the proposed method, the azimuth and elevation angles are estimated independently from the cross-correlation matrices between the received data of two ULA subarrays by linear operation, and then the pair-matching of estimated azimuth and elevation angles can be accomplished by using the correlation matrix of the combined received data of these subarrays. Since the eigen-decomposition is avoided, the proposed DOA estimation method has less computational complexity and better estimation performance than the existing methods. Furthermore the asymptotic mean-square-error (MSE) expressions of the estimation errors are derived, and the effectiveness of the proposed method is verified through numerical examples.

Near-field source localization with partly sensor gain and phase uncertainties

In this paper, we consider the source localization for the multiple near-field narrowband signals impinging on a uniform linear array (ULA) with partly gain and phase uncertainties. By dividing the ULA into two overlapped symmetric subarrays and assuming that they have partly unknown gain and phase responses but correspondingly identical, a new modified generalized ESPRIT based method is presented, in which the direction of arrival (DOA) and range are estimated separately. Moreover, we prove that the proposed method is equivalent to the spectral Fresnel-region rank reduction (FR-RARE) [15] method, but more computationally efficient than it. The simulations demonstrate the effectiveness of the proposed method.