Publications
151 results found
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.
Zhou Y, Adachi F, Wang X, et al., 2012, Broadband Wireless Communications for High Speed Vehicles, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol: VOL. 30, Pages: 673-674, ISSN: 0733-8716
Zhou Y, Adachi F, Wang X, et al., 2012, Broadband Wireless Communications for High Speed Vehicles, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol: 30, Pages: 673-674, ISSN: 0733-8716
Willerton M, Banavar M, Zhang X, et al., 2012, Sequential Wireless Sensor Network Discovery Using Wide Aperture Array Signal Processing, EUSIPCO 2012
In this paper, a novel wireless sensor network discovery algorithm is presented which estimates the position of a large number of low powered, randomly distributed sensor nodes. Initially, all nodes are at unknown locations except for a smallnumber which are termed the “anchor” nodes. The remaining nodes are to be located as part of the discovery procedure. As the locations of sensor nodes are estimated, they can be used in the localization of other nodes. Transmitting nodes in unknown locations are localized in a decentralized manner by using a set of receiving sensor nodes at known or estimated locations within its coverage area. This set of nodes forms an array which is used for localization. Initially a coarse localisation of all nodes is performed to identify their approximate positions. A fine grained localization procedure then follows for refinement. This paper will focus on the coarse localizationapproach. Simulations demonstrate the effectiveness of the proposed method.
Willerton M, Manikas A, 2012, Auto-Calibration of Sparse Arrays of Sensors, IEEE Transactions on Signal Processing
Manikas A, Kamil Y, Willerton M, 2012, Source Localisation using Large Aperture Sparse Arrays, IEEE Transaction on Signal Processing
In this paper, a novel source/target localization approach is proposed using a number of sensors (surrounding or not surrounding one or more sources) to form a large aperture sparse array of known geometry. Under a large array aperture, the array response (manifold vector) obeys a spherical wave rather than a plane wave propagation model. By rotating the array reference point to be at each of the array sensors, a number of covariance matrices are constructed based on the same set of data. It is shown that the eigenvalues of these covariance matrices are related to the source location with respect to the array reference point. The proposed approach is robust to channel fading and considers both wideband andnarrowband sources/targets. The performance of the proposed approach is evaluated via simulations as a function of array geometry, number of snapshots (L) and Signal to Noise Ratio (SNR) and shown to exceed existing techniques
Manikas A, Thomas PA, 2012, Multi-Sensor Signal Processing for Defence: Detection, Localisation & Classification, Iet Signal Processing, Vol: 6, Pages: 393-394
Talantzis F, Pnevmatikakis A, Constantinides AG, 2011, AUDIO-VISUAL PERSON TRACKING:A Practical Approach, ISBN: 978-1-84816-581-6
This book deals with the creation of the algorithmic backbone that enables a computer to perceive humans in a monitored space. This is performed using the same signals that humans process, i.e., audio and video. Computers reproduce the same type of perception using sensors and algorithms in order to detect and track multiple interacting humans, by way of multiple cues, like bodies, faces or speech. This application domain is challenging, because audio and visual signals are cluttered by both background and foreground objects. First, particle filtering is established as the framework for tracking. Then, audio, visual and also audio-visual tracking systems are separately explained. Each modality is analyzed, starting with sensor configuration, detection for tracker initialization and the trackers themselves. Techniques to fuse the modalities are then considered. Instead of offering a monolithic approach to the tracking problem, this book also focuses on implementation by providing MATLAB code for every presented component. This way, the reader can connect every concept with corresponding code. Finally, the applications of the various tracking systems in different domains are studied.
Commin H, Manikas A, 2011, Spatiotemporal Arrayed MIMO Radar: Joint Doppler, Delay and DoA Estimation, IEEE Transactions on Signal Processing
Estimating the parameters of multiple closely-spaced targets is a key topic in MIMO radar research. The key to designing and analysing an array system in general lies in understanding the array manifold, which completely charac- terises the geometry of the array system. The shape of the array manifold has a profound and fundamental importance and has been extensively investigated in the literature using differential geometry. However, until now, these methods have been applied only to the receiver array of the array system. Therefore, in MIMO radar (where there also exists an arrayed transmitter), it has not previously been possible to fully characterise the whole transmit-receive system geometry within such a framework. In this paper, an equivalent ‘virtual’ SIMO (Single Input Multiple Output) representation of the MIMO radar system is established which allows direct analysis of the full MIMO system geometry. By analysing the virtual array manifold, it is shown that the fundamental detection, resolution and estimation error bounds of the MIMO configuration are generally superior to any approach that only exploits receiver array geometry (with equal performance emerging as a worst case). By employing a special sequence of transmit waveforms, this virtual SIMO framework is then incorporated into a novel space-time receiver architecture which performs joint estimation of Doppler, relative path delays and direction of arrival (DOA). In this way, the effects of Doppler and path delays are not only mitigated, but used to actively enhance the capabilities of the parameter estimation system.
Efstathopoulos G, Manikas A, 2011, Extended Array Manifolds: Functions of Array Manifolds, IEEE Transactions on Signal Processing, Vol: 57, Pages: 3272-3287, ISSN: 1053-587X
Willerton M, Manikas A, 2011, Array Shape Calibration using a Single Multi-Carrier Pilot, Proceeding in Sensor Signal Processing for Defence (SSPD 2011) Sep 2011.
Willerton M, Manikas A, 2011, Virtual Linear Array Modelling of a Planar Array, Proceedings of IMA Mathematics in Defence
Manikas A, 2011, Corrigendum "Extended Array Manifolds: Functions of Array Manifolds"., IEEE Transactions on Signal Processing, Vol: 59, Pages: 4501-4501
Chen Z, Manikas A, 2010, Direction-of-departure estimation using cooperative beamforming, 7th International Symposium on Wireless Communication Systems (ISWCS), 2010
Zhuang J, Li W, Manikas A, 2010, Fast root-MUSIC for arbitrary arrays, ELECTRONICS LETTERS, Vol: 46, Pages: 174-175, ISSN: 0013-5194
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Zhuang J, Li W, Manikas A, 2010, AN IDFT-BASED ROOT-MUSIC FOR ARBITRARY ARRAYS, 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, Publisher: IEEE, Pages: 2614-2617, ISSN: 1520-6149
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- Citations: 6
Chen Z, Manikas A, 2010, Joint Space-Time Transmitter-Receiver Beamforming, IEEE Global Telecommunications Conference (GLOBECOM 2010), Publisher: IEEE, ISSN: 1930-529X
Commin H, Manikas A, 2010, The Figure of Merit “C” for Comparing Super-resolution Direction Finding Algorithms., Proceedings of Sensor Signal Processing for Defence (SSPD 2010), Sep 2010
Peh HH, Manikas A, Tjhung TT, et al., 2009, Joint Transmitter-Receiver Beamforming in Downlink Cyclic Prefix-Free Spatio-Temporal MC-CDMA, IEEE International Conference on Posted Online Date 11 Aug 2009
Peh HH, Manikas A, Tjhung TT, et al., 2009, Joint Transmitter-Receiver Beamforming in Downlink Cyclic Prefix-Free Spatio-Temporal MC-CDMA, International Conference in Communications
Li W, Kamil YI, Manikas A, 2009, Wireless array based sensor relocation in mobile sensor networks., Publisher: ACM, Pages: 832-838
Rashid F, Peh HH, Manikas A, 2008, Diffused Channel Estimation and Reception for Cyclic Prefix-free MC-CDMA Arrayed-MIMO Communication Systems, International Journal of Wireless Information Networks (Special Issue), Vol: 15, Pages: 148-160, ISSN: 1068-9605
Abstract: An arrayed-MIMO communication system, which employs antenna arrays at both ends of the wireless link is proposed to leverage upon spatial information such as directions-of-arrival to achieve an improvement in performance. This is in contrast with conventional MIMO systems, which typically assume multiple independent antenna elements at the transmitters and receivers. This paper focuses on an arrayed-MIMO communication system operating over a frequency selective fading channel and employs MC-CDMA as the modulation technique. However, in a departure from conventional MC-CDMA systems, cyclic prefixes or guard intervals are not used for the MC-CDMA system employed here so that valuable bandwidth is not wasted on cyclic prefixes or guard intervals. Localized scattering is assumed to occur for each multipath; hence the wireless channel is modelled as a diffused vector channel. A robust blind estimation method is presented to estimate the parameters of the spatially diffused channel, followed by reception based on these parameters. The feasibility of the proposed system is supported by simulation results.
Rashid F, Manikas A, 2008, Arrayed MC-CDMA reception in space-time diffused multipath vector channels., Wireless Communications and Mobile Computing (Special Issue), Vol: 8, Pages: 575-584
Multi-Carrier Code Division Multiple Access (MC-CDMA) is a modulation scheme that combines the advantages of OFDM and CDMA to provide robustness against frequency selectivity in wireless channels. Arrayed MC-CDMA systems combine MC-CDMA and antenna array technology to harness the spatial and temporal 'signatures' of received signals, thus making it possible to realize high transmission rates envisioned for next generation wireless communications. Localized scattering, which occurs for each multipath, motivates the frequency selective wireless channel to be modelled as a diffused vector channel. In this paper, space-time diffused vector channels for arrayed MC-CDMA systems are modelled and analysed. Simulation studies show that the use of this diffused channel modelling in arrayed MC-CDMA receivers yields better Bit Error Rate (BER) and SNIRout performance than receivers that ignore the presence of spatial and/or temporal diffusion. Copyright (C) 2007 John Wiley & Sons, Ltd.
Li W, Kamil YI, Manikas A, 2008, A Wireless Array Based Cooperative Sensing Model in Sensor Networks, IEEE Global Telecommunications Conference (GLOBECOM 08), Publisher: IEEE, ISSN: 1930-529X
Supakwong S, Manikas A, Constantinides AG, 2008, Analysis of Three-Parameter Diversely Polarized Array Manifold, 19th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Publisher: IEEE, Pages: 552-556
Supakwong S, Manikas A, Constantinides AG, 2008, Analysis of three-parameter diversely polarized array manifold., Publisher: IEEE, Pages: 1-5
Manikas A, Kamil YI, Karaminas P, 2008, Positioning in Wireless Sensor Networks using Array Processing, IEEE Global Telecommunications Conference (GLOBECOM 08), Publisher: IEEE, ISSN: 1930-529X
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