Direction Of Arrival Of Signals Research Articles

Joint Channel and DOA Estimation for Multicarrier CDMA Uplink Transmissions

The use of antenna arrays in wireless communications makes it possible to estimate the directions of arrival (DOAs) of impinging waveforms. The latter can be exploited to enhance channel estimation accuracy or as an input for advanced mobile positioning systems. In this paper, we consider the uplink of a multicarrier code-division multiple-access (MC-CDMA) network in which the base station is endowed with multiple receiving antennas arranged in a uniform linear array. Transmission takes place over a multipath channel, and the goal is the joint estimation of the channel responses and DOAs of the uplink signals. In doing so, we follow a maximum-likelihood (ML) approach and assume that users transmit orthogonal training sequences to facilitate the task of separating the signals. This way, all unknown parameters are estimated independently of each other with affordable complexity. Theoretical analysis and computer simulations are used to assess the performance of the proposed scheme and make comparisons with existing alternatives.

Direction of arrival estimation for uncorrelated and coherent signals with uniform linear array

A novel direction of arrival (DOA) estimation method is proposed with uniform linear array when uncorrelated and coherent signals coexist. The DOAs of uncorrelated signals are first estimated using a new method of modified total least squares estimation of signal parameters via rotation invariance techniques. Afterwards, the contributions of uncorrelated signals are eliminated and a new matrix is constructed based on the spatial difference matrix. Then, the coherent signals can be resolved by performing the forward spatial smoothing scheme on the new matrix. The proposed method can resolve more signals than the array elements with good performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

Direction-of-arrival estimation for uncorrelated and coherent signals with fewer sensors

A novel direction-of-arrival (DOA) estimation method with fewer sensors is proposed when uncorrelated and coherent signals coexist, and two effective criteria to estimate the number of uncorrelated and coherent signals are also developed. First, the DOA matrix is constructed. Then, the DOAs of uncorrelated signals can be estimated by these proposed criteria and the related eigenvalues of the DOA matrix. Secondly, with the eigenvectors of the DOA matrix, which are related to coherent signals, the coherent signals that belong to the multipath of different far-field sources can be resolved separately using a spatial smoothing technique. Moreover, the DOA estimation accuracy of coherent signals can be further improved by an orthogonal projection technique. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

Full Azimuth Direction-of-Arrival Estimation With Successive-Selection Technique

A method for full-azimuth direction-of-arrival (DoA) estimation of multiple signals with a hexagonal array is proposed. The DoA estimation is performed in two steps. In the first, a set of estimate candidates is constructed by gathering the estimates that are obtained from applying the low-computational-cost Unitary-ESPRIT algorithm to several translational invariances designed into a hexagonal array. In the second step, the DoA estimates are successively selected from the estimate candidate set by using a selection function. The proposed method removes the north-or-south signal membership ambiguity and the limitation on the number of estimable sources, problems common to any ESPRIT-based algorithm used with one translational invariance. Therefore, up to M-1 signal DoA estimations can be expected with an M- element hexagonal array in the full azimuth. The successive-selection approach is based on a selection function that uses an estimate of the signal's spatial correlation matrix to successively select the DoA estimates. For each DoA estimate selection, the already estimated signal components are removed from the correlation matrix. Such an approach is shown to actually allow the selection of suitable estimates from among a set of estimate candidates. Finally, the method's DoA estimation and resolution capabilities are demonstrated by computer simulation and comparison with the Cramer-Rao bound.

An Importance Sampling Maximum Likelihood Direction of Arrival Estimator

We present a new implementation for maximum likelihood (ML) estimation of the direction of arrival (DOA) of multiple narrow-band plane waves in noise. The proposed estimator can be applied to the estimation of DOAs of both deterministic and stochastic signals. In this paper, we discuss the estimation of DOAs for stochastic signals only. The proposed method uses a global optimization procedure to maximize the compressed likelihood function, which is a function of only the DOAs. The procedure is based on Monte Carlo importance sampling. It is shown via simulations that the method allows for estimation of DOAs at low angular separation and in situations for which other suboptimal techniques may fail. The improved performance of this method is due to its guaranteed convergence to a global maximum, which is not true for the iterative ML methods, as, for example, the WSF, MODE(X), and EM algorithms. We compare our method to the latter algorithms to show that the proposed method outperforms the iterative approaches for closely spaced narrow-band sources.

Robust adaptive beamforming algorithm based on Bayesian approach

The performance of adaptive array beamforming algorithms substantially degrades in practice because of a slight mismatch between actual and presumed array responses to the desired signal. A novel robust adaptive beamforming algorithm based on Bayesian approach is therefore proposed. The algorithm responds to the current environment by estimating the direction of arrival (DOA) of the actual signal from observations. Computational complexity of the proposed algorithm can thus be reduced compared with other algorithms since the recursive method is used to obtain inverse matrix. In addition, it has strong robustness to the uncertainty of actual signal DOA and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently approach the optimum. Simulation results show that the proposed algorithm is better in performance than conventional adaptive beamforming algorithms.

Enhanced Reactance-Domain ESPRIT Algorithm Employing Multiple Beams and Translational-Invariance Soft Selection for Direction-of-Arrival Estimation in the Full Azimuth

An enhanced reactance-domain estimation of signal parameters via rotational invariance techniques (RD-ESPRIT) algorithm is proposed for direction-of-arrival (DoA) estimation in the full-azimuth plane. Unlike the classical RD-ESPRIT algorithm, the proposed method employs a generalized RD correlation matrix combined with soft selection. The proposed algorithm is expected to allow estimating more than one signal DoA with improved estimation precision. The generalized RD correlation matrix is formed by utilizing a number of beam patterns greater than or equal to the number of array elements. The soft selection employed in the enhanced RD-ESPRIT consists of two steps. First, the estimates obtained by applying the generalized RD-ESPRIT to three translational-invariance configurations are gathered to form a set of DoA estimate candidates. Second, selection functions based on a modified MUSIC function are used to select the DoA estimates from among the estimate candidate set. The proposed algorithm is investigated through computer simulations with a seven-element electronically steerable parasitic array radiator (ESPAR) antenna. The simulation showed that the proposed algorithm can perform effective DoA estimation of up to four incoming signals in the full-azimuth plane with slightly improved DoA-estimation precision. So far, the classical RD-ESPRIT is not effective because it can estimate up to one signal DoA. Moreover, the proposed method showed robust estimation capability for up to two incoming signals. A robust estimation refers to the fact that a number of DoA estimates equal to the number of incoming signals can always be selected from trial to trial. A one-signal estimation experiment was conducted in an anechoic chamber with a fabricated seven-element ESPAR antenna. In general, the proposed algorithm showed as accurate estimation precision as the classical algorithm. In particular, using soft selection instead of hard selection increases the estimation precision, whereas augmenting the number of beam patterns brings an increase in the estimation precision only when used with hard selection.

High Resolution DOA Estimation Using Unwrapped Phase Information of MUSIC-Based Noise Subspace

This paper presents a high resolution Direction-Of-Arrival (DOA) estimation method using unwrapped phase information of MUSIC-based noise subspace. Superresolution DOA estimation methods such as MUSIC, Root-MUSIC and ESPRIT methods are paid great attention because of their brilliant properties in estimating DOAs of incident signals. Those methods achieve high accuracy in estimating DOAs in a good propagation environment, but would fail to estimate DOAs in severe environments like low Signal-to-Noise Ratio (SNR), small number of snapshots, or when incident waves are coming from close angles. In MUSIC method, its spectrum is calculated based on the absolute value of the inner product between array response and noise eigenvectors, means that MUSIC employs only the amplitude characteristics and does not use any phase characteristics. Recalling that phase characteristics plays an important role in signal and image processing, we expect that DOA estimation accuracy could be further improved using phase information in addition to MUSIC spectrum. This paper develops a procedure to obtain an accurate spectrum for DOA estimation using unwrapped and differentiated phase information of MUSIC-based noise subspace. Performance of the proposed method is evaluated through computer simulation in comparison with some conventional estimation methods.

Development of an ocean surveillance system

Now‐a‐days, underwater sensor networks are gaining considerable importance, for Ocean Surveillance applications. A minimally configurable three‐node sensor network is found to be capable of performing localization as well as tracking of underwater targets. Each node comprises of a surface buoy having processing modules, controller hardware and support electronics for estimating the direction of arrival. The development of the node system comprising of controller and processing modules is presented in this paper. The controller hardware, consisting of a gear assembly, magnetic compass and a precision digital signal controller, helps in sampling the ocean by way of steering the hydrophone arrays and capturing the target emanations, while the processing module performs the computation of the direction of arrivals. The target emissions picked up by the hydrophone arrays are analyzed and processed for computing the direction of signal arrival with reference to the geomagnetic meridian. The direction of maximum...

BLIND DIRECTION OF ARRIVAL ESTIMATION OF COHERENT SOURCES USING MULTI-INVARIANCE PROPERTY

Blind direction of arrival (DOA) estimation algorithms of coherent sources using multi-invariance property is presented in this paper. ESPRIT-like algorithm in (23) can estimate DOA of coherent signal, but its performance is without satisfaction. We reconstruct the received signal to form data model with multi-invariance property, and then multi-invariance ESPRIT and multi-invariance MUSIC algorithms for coherent DOA estimation are proposed in this paper. Our proposed algorithms can resolve the DOAs of coherent signals. They have much better DOA estimation performance than ESPRIT- like algorithm. Meanwhile they identify more DOAs than ESPRIT-like algorithm. The simulation results demonstrate their validity.

Complex-valued ICA utilizing signal-subspace demixing for robust DOA estimation and blind signal separation

This paper deals with direction of arrival (DOA) estimation and blind signal separation (BSS) based on independent component analysis (ICA) with robust capabilities. An efficient demixing procedure of complex-valued ICA is presented here, which combines the signal-subspace demixing procedure exploiting individual signal-subspace projection and Newton's iteration algorithm based on maximization of the approximate negentropy of non-Gaussian signal for array signal processing. It resolves the problems of order ambiguity and identifiability of traditional ICA for time-domain BSS. The proposed method could be directly applied to radar, sonar, radio surveillance, and communications systems for separating signals and estimating relative DOAs of signals. Several computer simulation examples for perturbations to the array manifold, unknown noise environments, and Rayleigh fading channel are provided to illustrate the effectiveness of the proposed method.

An improved cyclic beamforming method for signal DOA estimation

Modulated signals used in telecommunication are cyclostationary. This property can be exploited to improve the direction of arrival (DOA) estimation performance. In this work, we propose an improved cyclic beamforming algorithm exploiting cyclostationarity. The proposed method exploits the information of both cyclic correlation matrix and cyclic conjugate correlation matrix with different cyclic frequencies. Compared with the existing methods, the simulation results show that proposed method improves substantially the signal selectivity; also it allows an increase in resolution power.

Direction of Arrival (DOA) Estimation Using Electrically Small Tuned Dipole Antennas

We present a methodology for the direction of arrival (DOA) estimation using the induced voltages that are measured at the loads connected to electrically small tuned dipole antenna arrays illuminated by the signal of interest (SOI). The matrix pencil method is applied directly to the induced voltages to estimate the DOA of the various signals. Using electrically small tuned antennas can be advantageous as they can be placed in close proximity of each other saving the real estate and, thus, making it possible to deploy phased arrays on small footprints. When dealing with closely spaced tuned electrically small antennas, it is necessary to use a transformation matrix to compensate for the strong mutual coupling that may exist between the antenna elements. The transformation matrix converts the voltages that are induced at the loads corresponding to the feed point of the array operating in the presence of mutual coupling and other near field scatterers to an equivalent set of voltages that will be induced by the same incident wave in an uniform linear virtual array (ULVA) consisting of omnidirectional isotropic point radiators equally spaced and operating in free space. For any given incident field, the open circuit voltage developed across the feed-point of the small dipole will always be less than the open circuit voltage developed across the feed-point of the half-wavelength dipole. The difference is in the voltage developed across the loads connected to the dipole's feed-point. With the small dipole antenna, the voltage developed across the load impedance will be orders of magnitude greater than the voltage developed across the load connected to the half-wavelength dipole, even though the power captured by any conjugately matched antenna is approximately the same irrespective of their lengths. Three different scenarios are presented to illustrate the methodology. First, we consider resonant dipole elements spaced half wavelength apart, electrically small tuned antenna elements spaced half wavelength apart and electrically small tuned antenna elements placed in close proximity of each other to reduce the footprint without affecting the performance of the phased array. In addition, we consider the possibility of DOA estimation using a combination of different type of electrically small antennas both uniformly and nonuniformly spaced. Numerical examples are presented to illustrate the principles of this methodology

Binaural speech enhancement by complex wavelet transform based on interaural level and argument differences

Binaural information might enhance speech signals in noisy environments. Most precedent studies in this area have implemented signal processing in time and frequency domains. For this study, an enhancement method using complex wavelet transform (CWT) was proposed. The CWT has a scale domain whose bandwidth is inversely proportional to the scale level and may therefore be well compared to auditory filters. The proposed processing procedure is the following: (1) By computing CWT for a sound signal at every direction of arrival (DOA), a database (DB) of the scale domain wavelet coefficients is prepared for every DOA. (2) For binaural input signals from an unknown direction, the scale domain wavelet coefficients are calculated using CWT. (3) The DOA of the input signal is estimated as the direction for which interaural level and argument differences calculated from wavelet coefficients are the most similar to those in the DB. (4) The input signal is segregated similarly to FDBM (Nakashima et al., 2003) based on the estimated DOA. Experiments with a directional target signal and an interference sound source calculated from real HRTFs were conducted to show the effectiveness of the proposed algorithm. [This research was partially supported by Sendai Intelligent Knowledge Cluster.]

Frequency domain blind source separation in a noisy environment

A prototype system for blind source separation (BSS) in a reverberant and noisy environment is presented. Our system uses a small three‐dimensional array with eight microphones and realizes BSS in various situations such as the separation of many speech signals located in a three‐dimensional space, and the extraction of primary sound sources surrounded by many background interferences. The mixed signals observed by the microphone array are processed by independent component analysis (ICA) in the frequency domain. The permutation problem is solved by normalized basis vector clustering, which is a generalized version of directions of arrival (DOA) clustering and has several advantages to the DOA based method. The system estimates the DOA of the source signals as a by‐product of the separation process. Moreover, the system has the ability to distinguish primary target signals and ambient noise. Our system performs an on‐the‐spot BSS of live recorded signals. Live demonstration will be performed at the meeting.

2-D unitary matrix pencil method for efficient direction of arrival estimation

In this study, we extended the one-dimensional (1-D) unitary matrix pencil method (UMP) [N. Yilmazer, J. Koh, T.K. Sarkar, Utilization of a unitary transform for efficient computation in the matrix pencil method to find the direction of arrival, IEEE Trans. Antennas Propagat. 54 (1) (2006) 175-181] to two-dimensional case, where 2-D matrix pencil (MP) method are used to find the 2-D poles corresponding to the direction of arrival (DOA), azimuth and elevation angles, of the far field sources impinging on antenna arrays. This technique uses MP method to compute the DOA of the signals using a very efficient computational procedure in which the complexity of the computation can be reduced significantly by using a unitary matrix transformation. This method applies the technique directly to the data without forming a covariance matrix. Using real computations through the unitary transformation for the 2-D matrix pencil method leads to a very efficient computational methodology for real time implementation on a DSP chip. The numerical simulation results are provided to see the performance of the method.

Ambiguity-function-based techniques to estimate DOA of broadband chirp signals

Various methods are available to perform direction-of-arrival (DOA) estimation for random sources. However, the work on DOA estimation of deterministic sources, such as broadband chirp signals, is quite limited. This paper proposes two novel methods for broadband chirp DOA estimation (BCD), namely the incoherent broadband chirp DOA estimation (BCD-I) and coherent broadband chirp DOA estimation (BCD-C). The proposed methods exploit the time-frequency structure of the chirp signal via the ambiguity function, which converts the absolute time and frequency of the chirp signal into relative time lag and frequency difference. The algorithms can be applied to arrays of any aperture size and arbitrary chirp rate signals. The signal frequency of the source can be higher than the conventional array design frequency, and the number of sources can be greater than the number of sensors as long as the signals are separable in the ambiguity function plane. These methods can be applied to single or multiple chirps with the same or different chirp rates. The performance analysis shows that our algorithms generally provide improvements in the DOA estimation of the broadband chirp sources.

Direction finding of deformed towed array in coherent signal environment

When the towing vessel was turned, the Directions-of-Arrival (DOA) estimation would be critically degraded if the horizontal towed linear array shape was still assumed to be a straight line. Especially to the coherent signals, which were frequently encountered in shallow water environment due to the multipath propagation, the DOAs could only be estimated by applying the Maximum Likelihood (ML) estimator with a priori information of the array geometry. In this paper, an effective method was proposed to simultaneously estimate the DOAs and the sensor positions of a bended towed array during a turn in the coherent signal environment, which was called the array shape self-calibration problem. Firstly, the spatial signature corresponding to the arbitrary number of incident coherent signals was blindly obtained from the output of the Constant Modulus (CM) array only based on the array sample data. Then the towed array shape calibration problem could be described as a nonlinear optimization problem and solved by Genetic Algorithm (GA). Once the towed array shape has been calibrated, the DOAs of coherent signals would be estimated subsequently by using the ML estimator. Finally, numerical examples were conducted to illustrate the effectiveness of the proposed method.

A matched filter bank based DOA estimation for asynchronous multipath CDMA channels

In this paper, a Direction Of Arrival (DOA) estimation algorithm is proposed for multiuser signals through uplink asynchronous multipath Code Division Multiple Access (CDMA) channels. The algorithm is based directly on the correlation matrices of matched filter bank outputs of desired user’s multipath signals and it does not require that the elements of base station antenna array outnumber the multipath signals, which is necessary for the conventional sub-space based direction-finding algorithm. Simulation results show that the proposed algorithm estimates the DOA of multipath signals effectively and acceptably. The proposed algorithm has the prominent advantages of low complexity, simpleness and practicality, which make it much more suitable for practical application.

Fast DOA estimation algorithm using pseudocovariance matrix

This paper proposes a new direction of arrival (DOA) estimation algorithm that can rapidly estimate the DOAs of incidence signals using a pseudocovariance matrix even under coherent interference environments. The conventional multiple signal classification (MUSIC) algorithm, which should estimate a covariance matrix, cannot perform a DOA estimation until it acquires the covariance matrix. In addition, the MUSIC algorithm cannot be used under rapidly changing or correlated interference environments. In contrast, the proposed algorithm can obtain a bearing response after acquiring the pseudocovariance matrix based on a single snapshot. Signal incidence angles can then be accurately estimated by combining the bearing response and the location of pattern nulls. Accordingly, the proposed algorithm can rapidly estimate the DOAs of signals even when they are correlated.