145 results found
Tang Z, Manikas A, 2020, Direction-of-arrival tracking of multiple fast-moving sources in antenna array based access networks, Athanassios Manikas, Publisher: Institute of Electrical and Electronics Engineers, ISSN: 0536-1486
This paper is concerned with the problem of simultaneously tracking the direction-of-arrival (DOA) of multiple fast moving sources using the vector-signal received by a small aperture antenna array of N elements. The antenna array may be located at the Node-B, eNode-B or gNode-B of an access network and is used in conjunction with a novel trajectory tracking algorithm. The proposed algorithm incorporates a “manifold extender” together with a state space model and an arrayed extended Kalman filter (EKF). These provide a spatiotemporal tracking approach of the DOAs and angular velocities of multiple fast moving sources snapshot-by-snapshot. Furthermore, two different manifold extenders are employed in the proposed algorithm and their performance is evaluated using computer simulation studies and is compared with the case where the proposed algorithm is implemented without a “manifold extender”.
Ren H, Manikas A, 2020, MIMO radar with array manifold extenders, IEEE Transactions on Aerospace and Electronic Systems, Vol: 56, Pages: 1942-1954, ISSN: 0018-9251
This paper is concerned with the problem of multi-target parameter estimation in arrayed Multiple-Input Multiple-Output (MIMO) radar. In particular, the radar operates in thepresence of moving targets, where the parameters of intereststo be estimated for each target are the relative delay, Dopplerfrequency, Direction-of-Arrival (DOA) and complex path coeffi-cients (or target’s radar cross section). Using the novel concept of“array manifold extender”, the dimensionality of the observationspace increases fromNtoNNext, making the radar morepowerful than conventional MIMO radar systems by handlingmore complex targets and estimating their parameters withincreased accuracy. Two “manifold extender” are proposed inthis paper in conjunction with a novel spatiotemporal subspace-type framework for estimating the target parameters. The per-formance of proposed framework is examined using computersimulation studies.
Tang Z, Manikas A, 2019, DOA and DOD Channel Estimation in MIMO Access Networks, IEEE ICC 2019, Publisher: Institute of Electrical and Electronics Engineers, ISSN: 0536-1486
This paper is concerned with MIMO techniques for 5G+ Access Networks. In particular, a joint Direction-of-Arrival (DOA) and Direction-of-Departure (DOD) estimation approach is proposed for MIMO systems that employ antenna arrays of N-elements at the transmitter (Tx) and N-elements at the receiver (Rx), both of known geometries. In the proposed system, a weight-vector of N orthogonal binary signals of length Nc is employed on the Tx-array, and then used at the Rx-array to extend the observation space of the received signals from N to NN. In the extended observation space the manifold vectors are functions of both the DOA and DOD. The proposed approach uses these extended manifold vectors, in conjunction with a superresolution subspace approach, to find the DOA and DOD of all the multipaths of the desired user in the presence of other multiple-access users, considering that all users transmit at the same time and in the same frequency band. The performance of the proposed approach is evaluated using computer simulation studies.
Luo K, Manikas A, 2017, Joint transmitter–receiver optimization in multitarget MIMO radar, IEEE Transactions on Signal Processing, Vol: 65, Pages: 6292-6302, ISSN: 1053-587X
Although, a significant attention has been drawn to the concept of multiple-input multiple-output (MIMO) radar and in particular on the transmit beamforming design and multitarget localization, the cooperation between Tx and Rx has been rarely investigated. In this paper, a novel joint Tx and Rx optimization approach for localization is proposed for MIMO radar where the transmit beamforming design and the estimation of the target's complex path gain are jointly derived by solving an optimization problem that takes account various target parameters. Moreover, the proposed transmit beamforming design controls the power distribution per individual target. The performance of the proposed method is evaluated using computer simulation studies and compared with techniques which simply combine Tx beamforming design with multitarget localization methods.
Gabillard T, Sridhar V, Manikas A, 2017, Capacity loss and antenna array geometry, IEEE International Conference on Communications (ICC), Publisher: IEEE, ISSN: 1938-1883
The impact of antenna array geometry on it’s ability to migrate interference, and hence the channel capacity, is a topic that is seldom studied and is crucial to future systems that will employ large arrays. In this paper, for the worst-case scenario where interferers are located spatially close to the desired users, the “capacity loss” is defined and expressed as a function of array geometry and propaganda environment. Based on the analytical results, simulation studies of the capacity loss are presented for different array geometries and various key insights on antenna array design are highlighted.
Wu J, Watson R, Bolla R, et al., 2017, Guest Editorial on Green Communications, Computing, and Systems, IEEE Systems Journal, Vol: 11, Issue:2, Pages: 546-550, ISSN: 1932-8184
Kamil Y, Manikas A, 2017, Multisource spatiotemporal tracking using sparse large aperture arrays, IEEE Transactions on Aerospace and Electronic Systems, Vol: 53, Pages: 837-853, ISSN: 0018-9251
In this paper, a multisource tracking technique is proposed using a sparse large aperture array of passive sensors of known geometry. First, a novel spherical-spatiotemporal-state-space model is introduced incorporating target ranges, directions, and Doppler effects in conjunction with the array geometry. Subsequently, this array of sensors is integrated with an extended Kalman filter (EKF), defined as the arrayed EKF, to track the trajectory of multiple mobile sources. In addition, a recursive lower bound on the performance of the proposed tracking method is obtained based on the posterior Cramer-Rao bound. Computer simulation studies show that the proposed approach can track the locations of sources, as these move in space, with a very high accuracy.
Venieris E, Manikas A, 2017, Near-far field multipath spatial-temporal localisation, IEEE International Conference on Communications 2017, Publisher: Institute of Electrical and Electronics Engineers, ISSN: 0536-1486
In this paper, a passive array processing algorithm isproposed for localising the near-far field multipaths of the desiredsignal in the presence of co-channel interference. By expressingthe unknown path delay as a function of the path’s range,the proposed spatiotemporal localisation algorithm estimates thelocations of all the multipath reflectors of the desired signalsource using a subspace-type cost function. The performance ofthe proposed algorithm is evaluated through computer simulationstudies.
Sridhar V, Manikas A, 2017, Target Tracking with a Flexible UAV Cluster Array, IEEE GLOBECOM 2016, Publisher: IEEE
Unmanned aerial vehicle (UAV) cluster applications,for tasks such as target localisation and tracking, are required tocollect and utilise the data received on “flexible” sensor arrays,where the sensors, i.e. UAVs in this scenario, have time-variantpositions. In this paper, using a parametric channel model, a UAVcluster mobility model and a kinematic model of the targets, anextended Kalman based state space model is proposed that tracksthe unknown UAV positions and target parameters snapshot bysnapshot. Simulation studies illustrating the tracking capabilitiesof the proposed technique have been presented.
Fang Z, Manikas A, 2017, DOA and Range Estimation of Multiple Sources Under the Wideband Assumption, IEEE GLOBECOM 2016, Publisher: Institute of Electrical and Electronics Engineers (IEEE), ISSN: 0895-1195
In this paper, two novel channel parameter estimationalgorithms are proposed under the “wideband assumption,”where a wavefront varies significantly when traversing throughthe sensors of the array. The first covariance-based approachutilizes the cross-covariance matrix between two subvectors of thereceived signal vector and the singular value decomposition to reconstructthe parameter-dependent signal subspace. Meanwhile,the second reference-based approach employs the rotation of thearray reference point so that the estimation techniques underthe “narrowband assumption” are readily applicable. Throughcomputer simulation studies, the two proposed approaches areshown to successfully estimate the channel parameters under thewideband assumption with outstanding accuracy in terms of theestimation root mean squared error
Fang Z, Manikas A, 2017, Arrayed space optical communications: localization of the ground station, IEEE International Conference on Communications (ICC), Publisher: IEEE
In this paper, a novel ground station localizationalgorithm is proposed for space optical communications using ar-ray processing and a set of celestial objects of known locations inthe global coordinate system. First, the ground station estimatesthe directions of this set of celestial objects relative to its localcoordinate system using the sunlight reflected by these celestialobjects. Then, the ranges of the celestial objects and the locationand orientation of the ground station are estimated by solvingsystems of nonlinear and linear equations. The performance ofthe proposed approach is assessed through computer simulationstudies. It is shown to estimate the location and orientation ofthe ground station successfully with excellent accuracy.
Liu Q, Manikas A, 2016, Experimental Comparison of Localisation Techniques in the Presence of Array Uncertainties, European Conference on Antennas and Propagation (EuCAP)
Sridhar V, Gabillard T, Manikas A, 2016, Spatiotemporal-MIMO channel estimator and beamformer for 5G, IEEE Transactions on Wireless Communications, Vol: 15, Pages: 8025-8038, ISSN: 1536-1276
With requirements of spiraling data rates and limited spectrum availability, there is an increased interest in mm-wave beamformer-based communications for 5G. For upcoming cellular networks, the critical point is to exploit the increased number of employable antennas at both Tx and Rx to: 1) combat increased path loss; 2) tackle higher interference due to higher user density; and 3) handle multipath effects in frequency selective channels. Toward this, a multi-beam spatiotemporal superresolution beamforming framework is proposed in this paper as a promising candidate to design beampatterns that mitigate/suppress co-channel interference and deliver massive gain in the desired directions. Initially, channel and signal models suitable for the mm-wave MIMO system are presented using the manifold vectors of both Tx and Rx antenna arrays. Based on these models, a novel subspace-based channel estimator is employed, which estimates delays, directions, velocities, and fading coefficients of the desired signal paths. This information is then exploited by the proposed spatiotemporal beamformer to provide a massive array gain that combats path loss without increasing the number of antenna array elements and to be tolerant to the near-far problem in a high interference environment. The performance of the proposed channel estimator and beamformer is examined using computer simulation studies.
Manikas A, Sridhar V, Kamil Y, 2016, Array of sensors: A spatiotemporal-state-space model for target trajectory tracking (Invited Paper), 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Publisher: IEEE, ISSN: 2151-870X
In this paper, with the objective of tracking the trajectoryof multiple mobile targets, a novel spatiotemporal-state-space modelis introduced for an array of sensors distributed in space. Underthe wideband assumption, the proposed model incorporates the arraygeometry in conjunction with crucial target parameters namely (i) ranges,(ii) directions, (iii) velocities and (iv) associated Doppler effects. Computersimulation studies show some representative examples where the proposedmodel is utilised to track the locations of sources in space with a veryhigh accuracy.
Gabillard T, Sridhar V, Manikas A, 2015, Comparative Study of 2D Grid Antenna Array Geometries for Massive Array Systems, IEEE GLOBECOM 2015, Publisher: IEEE
In upcoming trends of wireless communications, such as massive MIMO, the number of antennas at the transmitter(TX) and receiver (RX) are expected to increase dramatically, aiming to provide a substantial improvement in system performance and spectral efficiency. However, an increase in the number of antennas also results in an increase in hardware, computational complexity and energy dissipation of the MIMO system. Therefore, the antenna array geometry plays a crucial role in the overall system performance. This paper is concerned with planar antenna array geometries with emphasis given to the family of 2D "grid" arrays and presents an insight into the relation between the array geometry and various performance metrics, such as detection, resolution and data-rate maximization, that may be used in different applications.
Mak K, Manikas A, 2015, A superresolution wide null beamformer for undersampled signal reconstruction in SIMO SAR, IEEE Journal of Selected Topics in Signal Processing, Vol: 9, Pages: 1548-1559, ISSN: 1932-4553
With single-input single-output (SISO) SAR systems, employing a single transmitter and receiver beam, there exists ahigh resolution, wide swath contradiction. However, by using multiple receiver beams and employing array processing techniques, this contradiction can be overcome, allowing greater flexibility anda wider range of application requirements to be met. In this paper the use of single-input multiple-output (SIMO) SAR systems forovercoming this contradiction is of interest, and a novel beam-former is proposed for processing in the cross-range direction. Inorder to fully describe the system, the array manifold vector is utilized, which is a key concept in the design of the beamformer. In particular, this beamformer is a superresolution beamformer ca-pable of forming wide nulls using subspace based approaches andallows the suppression of ambiguities in multiple sets of received under sampled SAR data in the cross-range direction and reconstruction of the Doppler spectrum to form a single unambiguous set of SAR data. Compared to the existing reconstruction algorithm, only a single weighting vector is required for a block of ambiguous Doppler frequencies compared to a weight vector requiredfor each ambiguous Doppler frequency. The capabilities of the proposed beamformer are shown to give an improved performance inambiguity suppression via computer simulation studies in a representative maritime environment.
Commin H, Luo K, Manikas A, 2015, Arrayed MIMO Radar: Multi-target Parameter Estimation for Beamforming, Beamforming Sensor Signal Processing for Defence Applications, Editors: Manikas, Publisher: Imperial College Press, Pages: 119-158, ISBN: 978-1-78326-276-2
Sridhar V, Willerton M, Manikas A, 2015, Towed Arrays: Channel Estimation, Tracking and Beamforming, Beamforming Sensor Signal Processing for Defence Applications, Editors: Manikas, Publisher: Imperial Colege Press, Pages: 159-187, ISBN: 978-1-78326-274-8
Willerton M, Venieris E, Manikas A, 2015, Array Uncertainties and Auto-calibration, Beamforming - Sensor Signal Processing for Defence Applications, Editors: Manikas, Publisher: Imperial College Press, Pages: 221-262, ISBN: 978-1-78326-274-8
Zhuang J, Manikas A, 2015, Robust Beamforming to Pointing Errors, Beamforming - Sensor Signal Processing for Defence Applications, Editors: Manikas, Publisher: Imperial College Press, Pages: 263-286, ISBN: 978-1-78326-274-8
Mak K, Manikas A, 2015, Digital Beamforming for Synthetic Aperture Radar, Beamforming Sensor Signal Processing for Defence Applications, Editors: Manikas, Publisher: Imperial College Press, Pages: 63-117, ISBN: 978-1-78326-275-5
Manikas A, 2015, Beamforming - Sensor Signal Processing and Defence Applications, Publisher: Imperial College Press - Communications and Signal Processing Series, ISBN: 978-1-78326-274-8
This book is concerned with adaptive sensor array processing and in particular with superresolution beamformers and their applications to sonar and radar. In the book both narrowband and wideband beamformers will be presented as well as space-only and spatiotemporal beamformers, which may operate in the presence of clutters and jammers. Furthermore, transmitter (Tx), receiver (Rx) and both Tx/Rx (MIMO) beamformers will be considered and their role in radar and sonar designs will be discussed. Design, integration and auto-calibration approaches incorporating off-the-shelf components will be also presented.
Mak K, Manikas A, 2015, Beamforming for Wake Wave Detection and Estimation — An Overview —, Beamforming - Sensor Signal Processing for Defence Applications, Publisher: Imperial College Press, Pages: 159-187, ISBN: 978-1-78326-275-5
Venieris E, Manikas A, 2014, Preprocessing algorithm for source localisation in a multipath environment, Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th, Publisher: IEEE, ISSN: 1551-2282
Several methods have been developed which allow the estimation of the location of an existing source with considerable accuracy in the absence of multipaths. However, if, in addition to the Line-of-Sight (LOS) path, non-LOS (NLOS) paths are also present, then all existing localisation algorithms dramatically fail to estimate the location of the source. In this paper, a passive array processing algorithm is proposed, which, if used prior to a localisation approach, suppresses all the multipath contributions in the received signal except for that of the LOS path. The performance of the proposed algorithm is evaluated through computer simulation studies.
Akindoyin A, Willerton M, Manikas A, 2014, Localization and array shape estimation using software defined radio array testbed, Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th, Publisher: IEEE, Pages: 189-192
Efstathopoulos G, Manikas A, 2013, Existence and Uniqueness of Hyperhelical Array Manifold Curves, IEEE Journal on Selected Topics in Signal Processing, Vol: Special Issue on Differential Geometry in Signal Processing
Significant open issues in array processing have been successfully investigated based on the concept of the array manifold and taking advantage of our understanding of its physical geometrical shape in an N-dimensional complex space - using differential geometry. Array ambiguities, arrayuncertainties, array design and performance characterisation are just some of the areas that have benefited from this approach.Unfortunately, the investigation of the shape of the array manifold itself for most but a few array geometries has been proven to be extremely complex and restrictive - especially in the numberof geometric properties that can actually be calculated. However, special array geometries have been identified, for which the arraymanifold curve assumes a specific “hyperhelical” shape. This is one of the most important manifold shapes and its properties greatly simplifies its geometric analysis and, consequently, the analysis of the associated array os sensors. Hence, the goal of this paper is twofold: to provide the necessary and sufficient conditions for the existence of array manifold curves of hyperhelical shape; and to determine which array geometries can actually give rise to manifold curves of thisshape
Manikas A, Commin H, Sleiman A, 2013, Array Manifold Curves in C^N and their Complex Cartan Matrix, IEEE Journal of Selected Topics in Signal Processing, Vol: 7, Pages: 670-680, ISSN: 1932-4553
The differential geometry of array manifold curves has been investigated extensively in the literature, leading to numerous applications. However, the existing differential geometric framework restricts the Cartan matrix to be purely real and so the vectors of the moving frame U(s) are found to be orthogonal only in the wide sense (i.e. only the real part of their inner product is equal to zero). Imaginary components are then accounted for separately using the concept of the inclination angleof the manifold. The purpose of this paper is therefore to present an alternativetheoretical framework which allows the manifold curve in CN to be characterised in a more convenient and direct manner. A continuously differentiable strictly orthonormal basis is established and forms a platform for deriving a generalised complexCartan matrix with similar properties to those established under the previous framework. Concepts such as the radius of circular approximation, the manifold curve radii vector and the frame matrix are also revisited and rederived under this new framework.
Zhuang J, Manikas A, 2013, Interference Cancellation BeamformingRobust to Pointing Errors, Iet Signal Processing, Pages: 1-8, ISSN: 1751-9675
The conventional Wiener–Hopf beamformer is subject to substantial performance degradation in the presence ofsteering vector pointing errors. By removing the effects of the desired signal, the modified Wiener–Hopf beamformer avoidsthis problem but allows cochannel interferences to pass through in order to maximise the signal-to-noise ratio. In this study, anovel array beamformer is proposed, which not only reduces the effect of pointing errors, but also asymptotically providescomplete interference rejection. In particular, the proposed beamformer utilises a vector space projection method and employsa one-step computation for the desired signal power. Using this, the effects of the desired signal can be extracted to form thedesired-signal-absent covariance matrix. Thus, a weight vector orthogonal with the interference subspace can be constructed.Numerical results demonstrate the superior performance of the proposed beamformer in the presence of pointing errorsrelative to other existing approaches such as ‘diagonal loading’, ‘robust Capon’ and ‘signal subspace projection’ beamformers.
Luo K, Manikas A, 2012, Superresolution Multi-Target Parameter Estimation in MIMO Radar, IEEE Trans. on Geoscience and Remote Sensing, ISSN: 0196-2892
This paper is concerned with a MIMO radar operating in an environment with two or moreclosely located targets. In this scenario, mutual target interference is a serious problem for multitarget parameter estimation, reducing the performance of existing methods such as Least Square (LS), Capon and Amplitude-and-Phase-EStimation (APES). In contrast to previous methods where the overalleffects of mutual target interference is treated as "noise", in this paper, two methods for suppressing this interference are proposed. The first is based on a constrained optimisation problem that provides an iterative method. The second involves a novel non-linear optimisation based on a cost function of targets’ directions which is solved using the Biogeography-Based Optimisation (BBO) algorithm. The performance of both the proposed approaches are evaluated via computer simulation studies and shown to outperform existing methods.
Zhang X, Banavar MK, Willerton M, et al., 2012, Performance comparison of localization techniques for sequential WSN discovery
In this paper, the performance of different localization algorithms are compared in the context of the sequential Wireless Sensor Network (WSN) discovery problem. Here, all sensor nodes are at unknown locations except for a very small number of so called anchor nodes at known locations. The locations of nodes are sequentially estimated such that when the location of a given node is found, it may be used to localize others. The underlying performance of such an approach is largely dependent upon the localization technique employed. In this paper, several well-known localization techniques are presented using a unified notation. These methods are time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS), direction of arrival (DOA) and large aperture array (LAA) localization. The performance of a sequential network discovery process is then compared when using each of these localization algorithms. These algorithms are implemented in the Java-DSP software package as part of a localization toolbox.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.