Mutual coupling between antenna array elements will significantly degrade the performance of the array signal processing methods. Due to the Toeplitz structure of mutual coupling matrix (MCM), there exist some mutual coupling calibration algorithms for the uniform linear array (ULA) or uniform circular array (UCA). But few methods for other arrays. In this letter, we derive a new transformation formula for the MCM of the 7-elements hexagonal array (HA-7). Further, we extend two mutual coupling auto-calibration methods from UCA to HA by the transformation formula. Simulation results demonstrate the validity of the proposed two methods.

Direction of arrival (DOA) estimation has been a primary focus of research for many years. Research on DOA estimation continues to be immensely popular in the fields of the internet of things, radar, and smart driving. In this paper, a simple new two-dimensional DOA framework is proposed in which a triangular array is used to receive wideband linear frequency modulated continuous wave signals. The mixed echo signals from various targets are separated into a series of single-tone signals. The unwrapping algorithm is applied to the phase difference function of the single-tone signals. By using the least-squares method to fit the unwrapped phase difference function, the DOA information of each target is obtained. Theoretical analysis and simulation demonstrate that the framework has the following advantages. Unlike traditional phase goniometry, the framework can resolve the trade-off between antenna spacing and goniometric accuracy. The number of detected targets is not limited by the number of antennas. Moreover, the framework can obtain highly accurate DOA estimation results.

This paper proposes two accurate source-number estimation methods for array antennas and multi-input multi-output radar. Direction of arrival (DOA) estimation is important in high-speed wireless communication and radar imaging. Most representative DOA estimation methods require the source-number information in advance and often fail to estimate DOAs in severe environments such as those having low signal-to-noise ratio or large transmission-power difference. Received signals are often bandlimited or narrowband signals, so the proposed methods first involves denoising preprocessing by removing undesired components then comparing the original and denoised signal information. The performances of the proposed methods were evaluated through computer simulations.

This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.

We have developed a novel array configuration based on the combination of sum and difference co-arrays. There have been many studies on array antenna configurations that enhance the degree of freedom (DOF) of an array, but the maximum DOF of the difference co-array configuration is often limited. With our proposed array configuration, called “sum and difference composite co-array”, we aim to further enhance the DOF by combining the concept of sum co-array and difference co-array. The performance of the proposed array configuration is evaluated through computer simulated beamforming*.

This paper presents a method combining array signal processing and adaptive noise cancellation to suppress unwanted ambient interferences in in situ measurement of radiated emissions of equipment. First, the signals received by the antenna array are processed to form a main data channel and an auxiliary data channel. The main channel contains the radiated emissions of the equipment under test and the attenuated ambient interferences. The auxiliary channel only contains the attenuated ambient interferences. Then, the adaptive noise cancellation technique is used to suppress the ambient interferences based on the correlation of the interferences in the main and auxiliary channels. The proposed method overcomes the problem that the ambient interferences in the two channels of the virtual chamber method are not correlated, and realizes the suppression of multi-source ambient noises in the use of fewer array elements. The results of simulation and experiment show that the proposed method can effectively extract radiated emissions of the equipment under test in complex electromagnetic environment. Finally, discussions on the effect of the beam width of the main channel and the generalization of the proposed method to three dimensionally distributed signals are addressed.

The Localization of distributed sources has attracted significant interest recently. There mainly are two types of localization methods which are able to estimate distributed source positions: two-step methods and direct localization methods. Unfortunately, both fail to exploit the location information and so suffer a loss in localization accuracy. By utilizing the information not used in the above, a direct localization method of multiple distributed sources is proposed in this paper that offers improved location accuracy. We construct a direct localization model of multiple distributed sources and develop a direct localization estimator with the theory of multiple signal classification. The distributed source positions are estimated via a three-dimensional grid search. We also provide Cramer-Rao Bound, computational complexity analysis and Monte Carlo simulations. The simulations demonstrate that the proposed method outperforms the localization methods above in terms of accuracy and resolution.

We consider the problem of two-dimensional (2-D) angles of arrival estimation using a newly proposed structure of nonuniform linear array, referred to as nested coprime array with compressed inter-element spacing (CACIS). By constructing a cross-correlation matrix of the received signals, the nested CACIS exhibits a larger number of degrees of freedom. A two-step weighted l1-norm penalty strategy is proposed to fully utilize these degrees of freedom, where the weight matrices are constructed by MUSIC spectrum function and the threshold function, respectively. The proposed method has several salient advantages over the compared method, including increased resolution and accuracy, estimating many more number of sources and suppressing spurious peaks efficiently. Simulation results validate the superiority of the proposed method.

We propose a new direction-of-arrival (DOA) estimation method of wideband signals. In several decades, many approaches to estimate DOA of wideband signal sources have been proposed. Test of orthogonality of projected subspaces (TOPS) and Squared TOPS are the estimation algorithms to realize high resolution performance of closely spaced signal sources. These methods, however, are not suitable for DOA estimation of multiple signal sources, because the spatial spectrum calculated by Squared TOPS has some false peaks. Therefore, the authors have proposed the weighted squared TOPS (WS-TOPS) to suppress these false peaks by modifying the orthogonality evaluation matrix, WS-TOPS also achieves better DOA estimation accuracy than that of Squared TOPS. On the other hand, WS-TOPS has a drawback, it requires high computational complexity. Our new method can realize good DOA estimation performance, which is better than that of Squared TOPS, with low computational complexity by reducing the size of orthogonality evaluation matrix and the number of subspaces to be used. Simulation results show that the new method can provide high resolution performance and high DOA estimation accuracy with low computational complexity.

Recently, Doppler radars have been used in various applications from the detection and the classification of indoor human activities to the detection of airplanes. To improve both the degrees of freedom (DOF) and the estimation accuracy of the direction-of-arrival (DOA) of targets, multiple-input multiple-output (MIMO) radar has received much attention in recent years. The temporal spatial virtual array based on Doppler shift of a moving target has been one of methods to improve DOA estimation accuracy. However, the DOA estimation accuracy based on the method depends on the velocity and the direction of the target on which we focus. Also, the temporal spatial virtual array should be generated based on the information of the single target. Thus, it is difficult to implement the method if there are multiple targets. In this paper, we propose a new method that provides high accuracy of DOA estimation by using the temporal spatial virtual array without dependence on the velocity, the direction and the number of existing targets. We demonstrate the DOA estimation accuracy and the effectiveness of the proposed method via simulations.

We study the correlation matrix element properties in array signal processing and apply them to a Direction-Of-Arrival (DOA) estimation problem of coherent or highly-correlated sources for a Uniform Linear Array (ULA). The proposed algorithm is generally based on the relation between the elements of the array correlation matrix and does not need an eigendecomposition, iteration, or angular peak-search. The performance of the proposed method was evaluated through a computer simulation.

In this paper, an adaptive expansion strategy (AES) is proposed for multiple-input/multiple-output (MIMO) detection in the presence of circular signals. By exploiting channel properties, the AES classifies MIMO channels into three types: excellent, average and deep fading. To avoid unnecessary branch-searching, the AES adopts single expansion (SE), partial expansion (PE) and full expansion (FE) for excellent channels, average channels and deep fading channels, respectively. In the PE, the non-circularity of signal is exploited, and the widely linear processing is extended from non-circular signals to circular signals by I (or Q) component cancellation. An analytical performance analysis is given to quantify the performance improvement. Simulation results show that the proposed algorithm can achieve quasi-optimal performance with much less complexity (hundreds of flops/symbol are saved) compared with the fixed-complexity sphere decoder (FSD) and the sphere decoder (SD).

A directional array radiator is presented, the aim of which is to enhance the sound of the television in a particular direction and hence provide a volume boost to improve speech intelligibility for the hard of hearing. The sound radiated by the array in other directions is kept low, so as not to increase the reverberant level of sound in the listening room. The array uses 32 loudspeakers, each of which are in phase-shift enclosures to generate hypercardioid directivity, which reduces the radiation from the back of the array. The loudspeakers are arranged in 8 sets of 4 loudspeakers, each set being driven by the same signal and stacked vertically, to improve the directivity in this plane. This creates a 3D beamformer that only needs 8 digital filters to be made superdirective. The performance is assessed by means of simulations and measurements in anechoic and reverberant environments. The results show how the array obtains a high directivity in a reverberant environment.

This paper presents a method of synthesizing covariance matrix elements of array input signal for high resolution 2-D Direction-Of-Arrival (DOA) estimation via antenna (sensor) switching. Antenna array generally has the same number of array elements and receiver modules which often leads large receiver hardware cost. Two of the authors have already studied a way of antenna switching to reduce receiver cost, but it can be applied only for periodic incident signals like sinusoid. In this paper, we propose two simple methods of DOA estimation from sparse data by synthesizing covariance matrix elements of array input signal via antenna switching, which can also be applied to DOA estimation of antiperiodic incident signals. Performance of the proposed approach is evaluated in detail through some computer simulation.

In this paper, a method is introduced that can detect the number of incident signals (NIS) even there are fewer antennas than NIS. Previous works on NIS detection methods assumed that the number of antennas always exceeded NIS. In the DOA estimation field, the DOA estimation is possible, even if NIS exceeds the number of antennas, by extending the degrees of freedom of array (DOFA) using a modified array configuration, such as a nested array (NA). The information of NIS is required in advance to accurately estimate DOA, however, it has not been investigated deeply when NIS is larger than the number of antennas. In this paper, a NIS detection method based on the DOFA extending process using NA is proposed. One of the important issues in NIS detection is the detection metric. As one of the simple metrics, the ratio of adjacent eigenvalues (RAE) has been used. However, the direct application of RAE may not achieve adequate NIS detection performance. Therefore, we propose a metric based on the modified ratio of adjacent eigenvalues (MRAE) avoids the issue of RAE. Numerical results show that the metric based on MRAE can achieve proper NIS detection performance even if NIS is larger than the number of antennas.

This paper presents a simple 3-D array configuration for high-resolution 2-D Direction-Of-Arrival (DOA) estimation. Planar array structures like Uniform Rectangular Array (URA) or Uniform Circular Array (UCA) often well estimate azimuth angle but cannot well estimate elevation angle because of short antenna aperture in elevation direction. One may put more number of array elements to improve elevation angle estimation accuracy, however it will require very large hardware and software cost. This paper presents a simple 3-D array structure for high-resolution 2-D DOA estimation only by modifying the height of some array elements in a planar array. Based on the analysis of Cramer-Rao Lower Bound (CRLB) formulation and its dependency on the height of array elements, we develop a simple 3-D array structure which improves elevation angle estimation accuracy while preserving azimuth angle estimation accuracy.

A new near-field source localization algorithm based on a uniform linear array was proposed. The proposed algorithm estimates each parameter separately but does not need pairing parameters. It can be divided into two important steps. The first step is bearing-related electric angle estimation based on the ESPRIT algorithm by constructing a special cumulant matrix. The second step is the other electric angle estimation based on the 1-D MUSIC spectrum. It offers much lower computational complexity than the traditional near-field 2-D MUSIC algorithm and has better performance than the high-order ESPRIT algorithm. Simulation results demonstrate that the performance of the proposed algorithm is close to the Cramer-Rao Bound (CRB).

In this study, we propose a one dimensional (1D) based successive generalized sidelobe canceller (GSC) structure for the implementation of 2D adaptive beamformers using a uniform rectangular antenna array (URA). The proposed approach takes advantage of the URA feature that the 2D spatial signature of the receive signal can be decomposed into an outer product of two 1D spatial signatures. The 1D spatial signatures lie in the column and the row spaces of the receive signal matrix, respectively. It follows that the interferers can be successively eliminated by two rounds of 1D-based GSC structure. As compared to the conventional 2D-GSC structure, computer simulations show that in addition to having significantly low computational complexity, the proposed adaptive approach possesses higher convergence rate.

A novel algorithm is presented for near-field source localization with a symmetric uniform linear array (ULA) consisting of an even number of sensors. Based on element reordering of a symmetric ULA, the steering vector is factorised with respect to the range-independent bearing parameters and range-relevant 2-D location parameters, which allows the range-independent bearing estimation with rank-reduction idea. With the estimated bearing, the range estimation for each source is then obtained by defining the 1-D MUSIC spectrum. Simulation results are presented to validate the performance of the proposed algorithm.

Hop-timing detection is of extreme importance for the reception of frequency hopping (FH) signals. Any error in the hop-timing detection has a deleterious effect on the performance of the receiver in frequency hopping (FH) communication systems. However, it is not easy to detect the hop-timing under low signal to noise power ratio (SNR) environments. Adaptive array antennas (AAA) have been expected to improve the performance of FH communication systems by beamforming for the direction of arrival of the desired signal. Since the conventional AAA exploits at least the coarse synchronization for dehopping of FH signals before achieving the beamforming, any fault in the hop-timing detection causes the deterioration of the performance of AAA. Using AAA based on the constant modulus algorithm (CMA), this paper proposes a new method for blind beamforming and hop-timing detection for FH signals. The proposed method exploits both the spatial and temporal characteristics of the received signal to accomplish the beamforming and detect the hop-timing without knowing any a priori information such as fine/coarse time synchronization and training signal. The performance verifications of the proposed method based on pertinent simulations are presented.