Earticle

Up to date, investigation of direction of arrival (DOA) gains more effort on multiple signals rather than coherent signals, particularly coherent signals measured by non-uniform and circular arrays ? which still remains room for exploration. In this study, a new approach using element transposition of the covariance matrix combined with the MUSIC algorithm was proposed to estimate DOAs of multiple coherent and non-coherent signals by an arbitrary symmetric antenna array. A balanced property of phase differences of the symmetric antenna array was discovered to de-correlate the received signals, and simulation was performed for linear and circular arrays. Here, we established a new method to estimate and distinguish the DOAs of both non-coherent and coherent signals with higher accuracy and resolution than other conventional methods.

Perturbation analysis of direction of arrival (DOA) estimation has been studied mostly on one-dimensional arrays rather than planar arrays, which remains room for exploration. For uniform circular arrays with various model errors, we establish the corresponding system model. Then a performance analysis of the two-dimensional MUSIC algorithm is proposed by first-order error analysis and verified by simulation. The results show that the root-mean-squared error of DOA estimation is proportional to the standard deviation of the model errors, including gain-phase errors, sensor position errors, and mutual coupling effect.

For subnanosecond low intensity of wireless network signal with representative Beidou Satellite navigation signal is difficult to obtain accurate time estimation and Angle estimation in the positioning, and easy to be affected by environmental noise, which made its positioning accuracy not higher, this paper proposed a parameter estimation method based on low intensity wireless network receiving signal spectrum. By sampling approach, first sampling launch signal as multidimensional independent sub-signal and modeling independently, through constructing noise space and sub-single space to obtain TOA estimation accurately based on the orthogonalization of corresponding column vector; then using complex domain mapping, on the basis of obtained TOA estimation, to obtain DOA estimation with contrast way accurately. Finally, it conducted accuracy analysis of the proposed parameter estimation method. Test data showed that: compared with PM algorithm, ESPRIT algorithm, the proposed technique was more accurate on TOAand DOA estimation; and in case of low strength of signal and serious background noise, the proposed method can still be effective to maintain the precision of parameters estimation. The technology can effectively reduce the influence of background noise on the signal transmission, has strong practical deployment significance.

In this paper, an improved adaptive monopulse scheme based on modified projection approximation subspace tracking deflation (MPASTd) approach is proposed. Owing to the fast convergence speed of MPASTd for recursively estimating the interference subspace, the proposed algorithm can obtain the formula for adaptive monopulse ratio calculation by a subspace projection. Therefore, it is able to accurately estimate the source location using less training data and reduce the computational complexity significantly. The effectiveness and fast convergence speed of the proposed method is verified by simulation results.

A new direction-of-arrival estimation method for uncorrelated wideband sources is proposed. Firstly, the covariance matrices of different frequency bins are transformed into higher dimensional vectors through Khatri-Rao product to produce the new models of the array outputs. Secondly, the higher dimensional noiseless signal subspace at each frequency is focused to a certain reference frequency and a single correlation matrix is constructed, where the focusing matrices are designed by interpolating the virtual steering matrices of the new model. Finally, the DOA estimates are acquired through using narrowband MUSIC method. The proposed method is able to increase the degrees of freedom of a uniform linear array and enable us to handle more sources than sensors. Numerical results demonstrate the performance of the proposed method.

Smart Adaptive Array antenna can automatically track the unknown interference signal in real time applications, that it requires to provide nulls towards the interference and offer gain to the required signal to ensure the required signal reception, so it leads the output SINR (signal to Interference and Noise Ratio) is improved. There is a growing need for the development of efficient algorithms for real-time optimization. Several algorithms can be applied for Digital Signal Processors (DSP), which differ in their complexity, convergence and so on In this paper, an efficient method for the DOA estimation of the linear antenna arrays with the prescribed steering and nulling lobe is presented. The proposed method is based on Least Mean Square (LMS) algorithm; provide a comprehensive and detailed treatment of the signal model used for beam forming, as well as, describing adaptive algorithms to adjust the weights of an array. In order to improve the convergence rate of LMS algorithm in smart antenna system, this paper proposes the GNGD algorithm. By taking advantage of spatial filtering, the proposed scheme promises to reduce the bandwidth required for transmitting data by improving convergence rate. The performance of the GNGD algorithm in the presence of Multi-path effects and multiple users is analyzed using MATLAB simulations. The simulations when compared to that of the LMS algorithm greater improvement in the convergence rate are observed. The results suggest that GNGD algorithm can improve the convergence rate and lead to better system efficiency.

The performance of the DOA algorithm and many other high resolution methods degrades severely with the high correlated multipath signals encountered in target low angle tracking. DOA estimation error is overcome by deriving new version of the effects model error and sensitivity analysis on subspace methods. An improved algorithm for DOA estimation of coherent signal is proposed. This algorithm has based on the structure of mutual coupling matrix of uniform linear array and effects model error sensitivity analysis. The performance of these two approaches is then compared with that of the well-known MUSIC algorithm using spatial smoothing. Through simulation, we show that the proposed method offers significantly improved estimation resolution and accuracy relative to existing method.

In this paper we propose an improved MUSIC (Multiple Signal Classification) algorithm applicable for direction of arrival (DOA) estimation of coherent signals in the presence of one-dimensional uniform linear array (ULA), which is based on Toeplitz matrix theory and Fourth-order-cumulants (Foc). In the signal model, a new Toeplitz construction method combining SVD (singular value decomposition) with mean calculation is explored to reconstruct the covariance matrix of array output. The DOA estimation problem can be addressed when the covariance matrix is full-rank. Foc theory is used to eliminate the Gaussian noise in the signals, after that the space of the array matrix is changed, which determines the final signal subspace and noise subspace. According to the subspace, we can adopt the conventional MUSIC to estimate the DOAs of coherent signals. Simulation results show that this algorithm provides a significant performance in comparison with other de-correlation algorithms. It has a better resolution under the condition of small angle interval. In addition, a lower root-mean-square error (RMSE) is obtained at low signal-to-noise (SNR) situation.

Recently, Compressive Sensing (CS) has been applied to array signal processing. In theory, Direction-of-Arrival (DOA) estimation based on CS recovery can work well in correlated environments. However, a large number of sensors (i.e., linear measurements) are still needed for CS recovery. To improve on this, we propose a new CS-based DOA estimation method with a recently designed antenna structure called the Asymmetric Antenna without Phase Center (Asym-AWPC). The best reconstruction is achieved by solving the l1-norm optimization problem, which is cast as an l1-regularized least-squares program. Simulated results indicate the effectiveness of the proposed CS-based Asym-AWPC DOA estimator in a multipath environment over a recent Asym-AWPC DOA estimator but using the Multiple Signal Classification (MUSIC) rather than CS. Further improvement on the resolution can be achieved by tuning the degree of asymmetry in designing the Asym-AWPC.

When the uniform circular array (UCA) is used to estimate the direction-of-arrival (DOA) of the coherent sources, it is necessary to transform the UCA data to the interpolated uniform linear array (ULA) data. Thus, the transformed array data can be applied to the spatial processing algorithm for the coherent sources such as the forward -backward smoothing algorithm. To select a more robust transformation matrix, a modified denoise approach for UCA estimation in low SNR case is proposed in this paper. First, a denoise method is investigated to maximize the SNR in the process of the interpolated transformation. The pseudo signal to noise ratio (PSNR) obtained from the eigenvalues of the forward-backward smoothing virtual covariance matrix estimate is used as the parameter of this maximization problem. Second, a modified maximization problem and its solution are presented to obtain more accurate estimates. The simulation results demonstrate the effectiveness of the proposed method, which improve the resolution ability and the estimation accuracy of the coherent sources in the low SNR case at the same time.

MUSIC algorithm has often used to solve the direction of arrival estimation problem to take advantage of the benefits of beamspace operations, such as reduced computation complexity, reduced sensitivity to system errors, good resolution, reduced bias in the estimation. In this paper, a variant of the beamspace MUSIC algorithm is developed, taking advantage of unitary transformations. In general, the beamspace MUSIC algorithm improves direction of arrival estimation by using reduced order characteristic polynomial rooting though Gaussian column reduction. The unitary beamspace MUSIC algorithm reduces the computational complexity of MUSIC algorithm by using real valued forward and backward, while maintaining the original precision. We use forward backward spatial smoothing technique as the preprocessor of beamspace MUSIC algorithm to recover the reduced rank of the covariance matrix due to the coherence of source signals. Through computer simulations show that the combination of spatial smoothing a beamspace MUSIC can achieve good resolution performance.

To extract the direction of arrival of multiple sensors from analysis data by a sensor array is a multiple parameter estimation problem. Some important algorithms for spatial temporal processing have been developed in the past decades. A new direction of arrival estimation method using effects of model errors and sensitivity analysis is proposed. Two subspace are used to form a signal space whose phase shift between the reference signal and its effects of model error signal. Since a desired signal is obtained after interference rejection through correction effects of model error, the effect of channel interference on the estimation is significantly reduced. The proposed method in the number of signal sources detectable is not bounded by the number of antenna elements used. Through simulation, we show that the proposed method offers significantly improved estimation resolution and accuracy relative to existing method.

본 논문은 W-CDMA 신호를 대상으로 3차원 적응 배열 안테나를 이용한 도래각 추정의 성능에 관한 것이다. 이를 위하여 5 가지의 3 차원 배열 안테나를 제시한 후 이들 안테나에 도래각 추정을 위한 알고리즘으로는 MUSIC을 공통으로 적용하였고, 이의 추정 성능을 위해서는 도래각 추정 오차를 이용하였다. 이동 통신과 무선 측위 서비스에서는 배열 안테나를 사용하여 방해 신호의 도래각을 추정한 후 공간 필터링하므로서 원하지 않는 방향으로부터의 방해 신호를 최소화 또는 널링시키고, 원하는 방향으로의 빔을 형성하므로서 수신 신호의 품질을 개선할 수 있다. 컴퓨터 시뮬레이션을 통해 안테나별 도래각 추정 결과와 신호대 잡음비와 방해 신호의 수와 전력에따른 도래각 추정 오차를 계산하였다. 시뮬레이션 결과 도래각 추정의 경우 Stack 3D 형을 제외한 나머지 3D 안테나가, 도래각 추정 오차의 경우 방해 신호의 수와 전력이 증가할때 Curved-B 형 안테나가 가장 우수함을 알 수 있었다.

This paper deals with the estimation performance DoA (Direction of Arrival) using the 3D adaptive array antenna in W-CDMA signal. For this, we proposed the 5 types of 3D array antenna, and appied for the MUSIC in order to the estimation of DoA algorithm for that antenna, commonly, then the DoA estimation error was used for the estimation performance. In the mobile communication and radio positioning service, performing the spatial filtering after the DoA estimation in array antenna, the quality of receiving signal can improve by the nulling or minimization of interfering signal which is from the undesired direction and the forming of beam which is from the desired direction. The result of DoA estimation and the DoA estimation error by varying the signal to noise ration and the number of interfering signal and power of each type antenna was calculated by computer simulation. As a result of simulation, the other propose antenna has good performance excluding the stack 3D antenna in DoA estimation and the Curved-B type antenna has more superior performance when increasing the number of interfering signal and power in the DoA estimation error.

Nowadays adaptive technique allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. So the interpolation of data from a given antenna array onto the output of a virtual array is needed before the direction finding technique is applied to the outputs of a uniform linear virtual array (ULVA). In this paper some superresoluntion methods are used to estimate DOA by best-fit transformation matrix T under different nonuniformly spaced array.

In this paper, a new method is proposed for tracking the direction-of-arrival (DOA) of the wideband moving source incident on uniform linear array sensors. DOA is estimated by focusing transformation matrices. To update focusing matrices along with new data snap shots, we use the FAST (Fast Approximate Subspace Tracking) method. Present focusing matrices are constructed by previous signal and its orthogonal basis vectors as well as present signal and its orthogonal basis vectors, which are the left and right singular vectors of the inner product of two approximated matrices. Simulation results are shown to illustrate the performance of the proposed method.

In this paper, a mobile relay station (MRS) for vehicles with a beamforming antenna is considered to increase the reliability of the transmission link, particularly for the MRS at the cell boundary. A cell searching and direction-of-arrival estimation method for an MRS with a uniform linear array is proposed for OFDM-based cellular systems in a multipath environment, even with the existence of the symbol timing offsets and carrier frequency offsets. The performance of the proposed method is evaluated by computer simulation using the standard profile of IEEE 802.16e.

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

A new computationally efficient algorithm-based propagator method for two-dimensional (2-D) direction-of-arrival (DOA) estimation is proposed, which uses two parallel uniform linear arrays. The algorithm takes advantage of the special structure of the array which enables 2-D DOA estimation without pair matching. Simulation results show that the proposed algorithm achieves very accurate estimation at a computational cost 4 dB lower than that of standard methods.

소나나 레이더분야에서의 방위 정보 추정에 있어서 직접신호와 반사신호가 있는 경우의 연구가 많이 이루어져왔다 특히 반사 신호 성분 중에 직접신호와 상관도가 높은 성분이 있는 스펙큘러 반사 성분이 있는 경우에 대한 연구가 많이 이루어져왔다. 이런 연구들은 대부분이 Block 데이타 처리 구조를 가지고 있다 따라서 방위가 시간에 따라서 변하는 경우 이런 Block 처리 구조를 가지고 처리하는 것은 오류를 범할 가능성이 높다. 본 논문에서는 recursive 구조를 갖는 알고리즘을 스펙큘러 환경에 강하도록 수정하여 시간에 따라 방위가 변하는 환경에 적용할 수 있도록 만든 알고리즘을 제안한다.