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For several years, a substantial effort has been devoted to the study of 3-D source localization based on 2-D arrays by measuring the well-known azimuth and elevation angles. However, studies on 3-D source localization performed by 1-D arrays are still lacking. Perhaps, the most important drawback in the deployment of a 2-D array structure lies in the fact that it needs a planar space, which might not be available in some applications. This letter concentrates on the problem of 3-D source localization based on 1-D angle measurement provided by a linear array. Different from the traditional 2-D structures where each measurement induces a straight line, each measurement in the 1-D array... 

In this paper, we study the problem of estimating the direction of arrival (DOA) using a sparsely sampled uniform linear array (ULA). Based on an initial incomplete ULA measurements, our strategy is to choose a sparse subset of array elements for measuring the next snapshot. Then, we use a Hankel-structured matrix completion to interpolate for the missing ULA measurements. Finally, the source DOAs are estimated using a subspace method such as Prony on the fully recovered ULA. We theoretically provide a sufficient bound for the number of required samples (array elements) for perfect recovery. The numerical comparisons of the proposed method with existing techniques such as atomic-norm... 

In this letter, the problem of non-coherent direction of arrival (DOA) estimation is investigated exploiting the sign of the measurements in order to resolve the inherent ambiguity of the problem. Although the phase values are inaccurate, the sign of real and imaginary parts of the measurements will most likely remain correct under limited phase errors. Furthermore, a new approach for solving the problem is proposed employing a modified version of the Majorization-Minimization (MM) technique, without any prior information about the number of incident signals. Some theoretical analyses of our proposed algorithm are also provided in the paper. Finally, the simulation results are presented,... 

This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval (MHR). This algorithm resolves problems, removes limitations of sampling and provides a more robust beamformer. A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer (SHRB). Simulation results show that SHRB has a better performance, accuracy, and applicability and more powerful eigenvalues than conventional beamformers. A simple mathematical proof is provided. By changing the number of harmonics, as a degree of freedom that is missing in conventional beamformers, SHRB can achieve more optimal outputs... 

In this article, an algebraic solution for localizing a moving target using a nonstationary multistatic radar system is proposed. By utilizing the quadruple hybrid measurement set, which consists of time delay, Doppler shift, angle of arrival, and angle rate measurements, the proposed method can estimate the target position and velocity vectors via a simple one-stage weighted least squares estimator without the need for introduction of the nuisance parameters, which enables us to locate the target with the minimum number of antennas. The proposed estimator takes the uncertainty concerned with the position and velocity of the antennas in its design. The proposed estimator is shown to be... 

The main task of a reconnaissance receiver is to acquire wide-band radio signals of the environment and extract their important parameters/information. Direction of arrival (DOA) and carrier frequency are the two most important parameters that a reconnaissance receiver should extract. To extract internal information of the signals such as signal modulation and coded information, complete reception of the signals is necessary. Sub-Nyquist sampling is used in this study for signal conversion from analog to digital with a much reduced sampling rate compared to the carrier frequency and, phase interferometery is used for direction finding. In jointly designing of sub-Nyquist sampling and phase... 

This paper uses the shift-invariance property of uniform linear array in root-MUSIC estimator for obtaining signal and noise subspaces by applying multistage Wiener filter (MSWF) procedure. Also, the MSWF root-MUSIC based on the pseudo-noise resampling process for estimating the direction of arrival (DOA) of signals is proposed. By this process, a root estimator bank and a corresponding DOA estimator bank are constructed. Then, a hypothesis test is applied to the DOA estimator bank to detect the normal DOA estimators from abnormal DOA estimators called outliers. By averaging the corresponding root estimators of normal DOA estimators, the final DOAs can be determined more accurately. When all... 

The root-MUSIC algorithm is a popular method to estimate Angle of Arrival (AoA) as an extension of multiple signal classification (MUSIC). In this paper, we have proposed a novel solution for the root-MUSIC algorithm. The new method exhibits a much lower computational complexity, while maintaining the same theoretical performance as the root-MUSIC. © 2019 IEEE  

In this letter, an efficient estimator for 3-D target localization in distributed multiple-input multiple-output (MIMO) radars using time delay (TD) and angle of arrival (AOA) measurements is proposed. First, an approximately equivalent maximum likelihood (ML) estimation problem is formulated. Then, the aforementioned ML problem is recast into a convex optimization problem for which we derive a semi closed-form solution that eventually boils down to finding the roots of certain polynomials. Using numerical simulations, we demonstrate that the proposed estimator reaches the Cramer-Rao lower bound (CRLB) up to relatively high Gaussian measurement noise levels. Furthermore, the proposed method... 

In this paper, we consider the problem of sensor placement for passive source localization under conditions where there are multiple sources and noise measurement is distance dependent. To this end, first we derive the Cramer-Rao bound for the angle of arrival (AOA) based source localization for distance-dependent noise model and existence of multiple sources. Then, the optimal arrangement of sensors to achieve this bound is obtained  

In this paper, we focus on the moving target localization problem in a multiple-input multiple-output radar with widely separated antennas. By exploiting jointly different types of information including time delay, Doppler shift and azimuth and elevation angles of arrival, we develop an algebraic closed-form two-stage weighted least squares solution for the problem. The proposed algorithm is shown analytically to attain the CramerRao lower bound accuracy under the small Gaussian noise assumption. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments  

In this paper, we propose an accurate visible light indoor localization system for a smartphone using the commercial light-emitting diode (LED) panels which are used primarily for lighting. Each of designed lighting panel contains a space-colorcoded identifier, a matrix with a unique pattern of spatially separated colored LEDs, for labeling different positioning cells while the lighting color is kept white by balancing the number of different sets of colored LEDs. The advantage of this idea is that we do not use the time-frequency domain of visible light communication (VLC) networks resources for positioning signaling. Our positioning technique called geometrical optics positioning algorithm... 

In this study, the optimal sensor placement problem for multi-source angle of arrival localisation is investigated. The authors adopt the A-optimality criterion, maximising the trace of Fisher information matrix, to determine the optimal sensor-target geometry under distance-dependent Gaussian noise model. A recursive representation of the Cramer-Rao lower bound is derived to recast the sensor placement problem into a sequential method, obtaining the optimal sensor geometries in a step by step manner. Note that the state-of-the-art methods are highly sensitive to the source location changes such that they should be relocated by any later changes in target geometries, which is practically... 

In this study, the optimal sensor placement problem for multi-source angle of arrival localisation is investigated. The authors adopt the A-optimality criterion, maximising the trace of Fisher information matrix, to determine the optimal sensor-target geometry under distance-dependent Gaussian noise model. A recursive representation of the Cramer-Rao lower bound is derived to recast the sensor placement problem into a sequential method, obtaining the optimal sensor geometries in a step by step manner. Note that the state-of-the-art methods are highly sensitive to the source location changes such that they should be relocated by any later changes in target geometries, which is practically... 

In this paper, a fundamental investigation on the performance of localization problem in a distributed multiple-input multiple-output radar system using bistatic range (BR) and angle of arrival (AOA) measurements is conducted. The study is based on the Cramer-Rao lower bound (CRLB) for the target position under Gaussian measurement noise. We attempt to approximately compute the CRLB separately in the cases of BR-only and joint BRlAOA localization schemes and determine which factors can affect the CRLB values. The three factors the transmitter/receiver placement, the number of transmitters and receivers, and noise power levels are shown to be effective on the localization performance.... 

The direction of arrival (DOA) error in dipole 3D arrays is estimated through Monte-Carlo simulations using the standard MUSIC algorithm. Novel 3D geometries are implemented which demonstrate better precision given the same lateral area. The mutual coupling effect is included by changing the search vector in the MUSIC DOA algorithm for the novel 3D geometries. A simple straight forward method is used which does not need complex electromagnetic computations. Simulations show that the proposed method can successfully account for the mutual coupling effects in two dimensional direction finding (both azimuth and elevation angle) with novel 3D array geometries. Reduced DOA estimation error is... 

In this paper, a property for sparse recovery algorithms, called invariancy, is introduced. The significance of invariancy is that the performance of the algorithms with this property is less affected when the sensing (i.e., the dictionary) is ill-conditioned. This is because for this kind of algorithms, there exists implicitly an equivalent well-conditioned problem, which is being solved. Some examples of sparse recovery algorithms will also be considered and it will be shown that some of them, such as SL0, Basis Pursuit (using interior point LP solver), FOCUSS, and hard thresholding algorithms, are invariant, and some others, like Matching Pursuit and SPGL1, are not. Then, as an... 

Numerous methods for direction of arrival (DOA) estimation, used in smart antennas have been already reported in previous studies. The precision of DOA estimation depends on the choice of the algorithm and the geometrical configuration of the antenna array. In this work, the performance of new geometrical configurations, i.e. 2D with equal area and 3D with equal volume including circular, square, triangular, hexagonal and star geometries, with equal number of antenna elements, are examined and compared to each other to find the most proper geometry. Monte-Carlo simulations are performed to evaluate the DOA precision of the proposed arrays using the MUSIC algorithm. It is shown that in three... 

In triangulation (or angle of arrival) target localisation method, the surface of the Earth is approximated by a flat plate. This approximation, while acceptable for low-altitude observers (such as unmanned aerial vehicles), is not a correct model for high-altitude observers (such as low Earth orbit - LEO satellites). In this study, the authors have discussed triangulation method using a LEO satellite observer over a spherical surface and have shown that, using spherical trigonometry and singular value decomposition (SVD), a straight forward solution can be found for target localisation problem. Also, error bound is discussed and analysed using both SVD as well as simulation. © The... 

The Cramer-Rao lower bound for source localization based on Time Difference of Arrival and Frequency Difference of Arrival is investigated in this paper. The result is used for theoretical analysis of optimality in sensor placement. An optimal sensor-target geometry including sensors locations and velocities is presented and its properties is studied