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Matrix Completion in Colocated MIMO Radar: Recoverability, Bounds & Theoretical Guarantees  [PDF]
Dionysios S. Kalogerias,Athina P. Petropulu
Computer Science , 2013,
Abstract: It was recently shown that low rank matrix completion theory can be employed for designing new sampling schemes in the context of MIMO radars, which can lead to the reduction of the high volume of data typically required for accurate target detection and estimation. Employing random samplers at each reception antenna, a partially observed version of the received data matrix is formulated at the fusion center, which, under certain conditions, can be recovered using convex optimization. This paper presents the theoretical analysis regarding the performance of matrix completion in colocated MIMO radar systems, exploiting the particular structure of the data matrix. Both Uniform Linear Arrays (ULAs) and arbitrary 2-dimensional arrays are considered for transmission and reception. Especially for the ULA case, under some mild assumptions on the directions of arrival of the targets, it is explicitly shown that the coherence of the data matrix is both asymptotically and approximately optimal with respect to the number of antennas of the arrays involved and further, the data matrix is recoverable using a subset of its entries with minimal cardinality. Sufficient conditions guaranteeing low matrix coherence and consequently satisfactory matrix completion performance are also presented, including the arbitrary 2-dimensional array case.
Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models  [cached]
Pesavento Marius,Mecklenbr?uker Christoph F,B?hme Johann F
EURASIP Journal on Advances in Signal Processing , 2004,
Abstract: A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE) algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.
Array independent MIMO channel models with analytical characteristics  [PDF]
Yuan Yao,Jianfeng Zheng,Zhenghe Feng
Mathematics , 2011,
Abstract: The conventional analytical channel models for multiple-input multiple-output (MIMO) wireless radio channels are array dependent. In this paper, we present several array independent MIMO channel models that inherit the essence of analytical models. The key idea is to decompose the physical scattering channel into two parts using the manifold decomposition technique: one is the wavefield independent sampling matrices depending on the antenna arrays only; the other is the array independent physical channel that can be individually modeled in an analytical manner. Based on the framework, we firstly extend the conventional virtual channel representation (VCR), which is restricted to uniform linear arrays (ULAs) so far, to a general version applicable to arbitrary array configurations. Then, we present two array independent stochastic MIMO channel models based on the proposed new VCR as well as the Weichselberger model. These two models are good at angular power spectrum (APS) estimation and capacity prediction, respectively. Finally, the impact of array characteristics on channel capacity is separately investigated by studying the condition number of the array steering matrix at fixed angles, and the results agree well with existing conclusions. Numerical results are presented for model validation and comparison.
Direction Finding for Bistatic MIMO Radar with Uniform Circular Array  [PDF]
Cao Yunhe,Zhang Zijing,Wang Shenghua,Dai Fengzhou
International Journal of Antennas and Propagation , 2013, DOI: 10.1155/2013/674878
Abstract: A method of direction of arrival (DOA) and direction of departure (DOD) angle estimation based on polynomial rooting for bistatic multiple-input multiple-output (MIMO) radar with uniform circular array (UCA) configuration is proposed in this paper. The steering vector of the UCA is firstly transformed into a steering vector with a Vandermonde structure by using the Jacobi-Anger expansion. Then the null-spectrum function of the MIMO radar can be written as an expression in which the transmit and receive steering vectors are decoupled. Finally, a two-step polynomial rooting is used to estimate DOA and DOD of targets instead of two-dimensional multiple signal classification (MUSIC) search method for bistatic UCA MIMO radar. The angle estimation performance of the proposed method is similar to that of the MUSIC spectral search method, but the computation burden of the proposed polynomial rooting algorithm is much lower than that of the conventional MUSIC method. The simulation results of the proposed algorithm are presented and the performances are investigated and analyzed. 1. Introduction Research on multiple-input multiple-output (MIMO) radar has been growing as evidenced by an increasing body of literature [1–10]. MIMO radar is characterized by using multiple antennas to simultaneously transmit orthogonal waveforms and multiple antennas to receive the reflected signals. MIMO radar has been shown to provide a number of potential benefits as compared with conventional radar, such as enhancing angle resolution, improving parameter identifiability, and increasing flexibility for transmit beam pattern design. In particular, the problem of multitarget localization in bistatic MIMO radar has received great research interests. Many methods in bistatic MIMO radar are proposed to identify and locate multiple targets [3–9] in which both the transmit array and the receive array are uniform linear arrays (ULAs). In order to avoid angle search, estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm is applied to bistatic MIMO radar [3–7] by exploiting the invariance property of the transmit and receive arrays. In [8, 9], several algorithms based on polynomial root finding procedure are proposed to estimate DOA and DOD of targets. Unfortunately, both the ESPRIT and the polynomial rooting method are designed for ULAs. The steering vector of the ULA is dependent on (where is the interelement spacing, is DOA of the source, and is the signal wavelength), and, hence, DOA estimation with ULA becomes ambiguous [10] beyond the range of 180°
MIMO Radar Array for Termite Detection and Imaging
Nick W. D. Le Marshall;Andrew Z. Tirkel
PIER B , 2011, DOI: 10.2528/PIERB10102802
Abstract: In this paper, we describe the design of a hybrid 24 GHz RADAR array for termite detection and imaging. The array uses MIMO techniques to provide transmit beam steering and null steering in conjunction with the Matrix Enhanced Matrix Pencil (MEMP), which provides direction of arrival processing. We describe the selection of our MIMO orthogonal codes and test their suitability. Simulated results are shown for our array design and MIMO processing in a range of applications MIMO enables us to produce flexible nulling and beam steering for our transmitter array as well as reducing multipath re°ections and narrowband interference. MIMO processing also produces large time savings, enabling longer, more accurate acquisitions which can increase SNR. Transmitter beam-forming, produces an SNR improvement of 18.2 dB and can be used to reject clutter by up to 20 dB. Flexible nulling can reject interferers still further.
Systolic Arrays for Lattice-Reduction-Aided MIMO Detection  [PDF]
Ni-Chun Wang,Ezio Biglieri,Kung Yao
Computer Science , 2011,
Abstract: Multiple-input, multiple-output (MIMO) technology provides high data rate and enhanced QoS for wireless com- munications. Since the benefits from MIMO result in a heavy computational load in detectors, the design of low-complexity sub-optimum receivers is currently an active area of research. Lattice-reduction-aided detection (LRAD) has been shown to be an effective low-complexity method with near-ML performance. In this paper we advocate the use of systolic array architectures for MIMO receivers, and in particular we exhibit one of them based on LRAD. The "LLL lattice reduction algorithm" and the ensuing linear detections or successive spatial-interference cancellations can be located in the same array, which is con- siderably hardware-efficient. Since the conventional form of the LLL algorithm is not immediately suitable for parallel processing, two modified LLL algorithms are considered here for the systolic array. LLL algorithm with full-size reduction (FSR-LLL) is one of the versions more suitable for parallel processing. Another variant is the all-swap lattice-reduction (ASLR) algorithm for complex-valued lattices, which processes all lattice basis vectors simultaneously within one iteration. Our novel systolic array can operate both algorithms with different external logic controls. In order to simplify the systolic array design, we replace the Lov\'asz condition in the definition of LLL-reduced lattice with the looser Siegel condition. Simulation results show that for LR- aided linear detections, the bit-error-rate performance is still maintained with this relaxation. Comparisons between the two algorithms in terms of bit-error-rate performance, and average FPGA processing time in the systolic array are made, which shows that ASLR is a better choice for a systolic architecture, especially for systems with a large number of antennas.
Conformal Antenna Array for MIMO Applications  [PDF]
Taha A. Elwi, Z. Abbas, Mohammed Noori, Yahiea Al-Naiemy, Ethar Y. Salih, Marwa M. Hamed
Journal of Electromagnetic Analysis and Applications (JEMAA) , 2014, DOI: 10.4236/jemaa.2014.64007

In this paper, a numerical study is reported based on the Finite Element Method (FEM) and the Finite Integral Technique (FIT) of Ansoft’s HFSS and CST Microwave Studio (MWS) formulations, respectively, applied to a Bended Complementary Split-Ring Resonator (BCSRR) of rejection band extending from 4.1 GHz to 4.6 GHz. The proposed BCSRR structure is combined with the design of a circularly polarized cylindrical antenna array of square patches with trimmed opposite corners. The performance of the cylindrical antenna array is characterized and compared to that of the flat profile. It is found that the proposed BCSRR reduces the mutual coupling to -15 dB between two patches with a separation of only 1/11th free-space wavelength for applications involving Multi Input Multi Output (MIMO) system.

Digital Array MIMO Radar and its Performance Analysis
Nirmalendu Bikas Sinha;Rabindra Nath Bera;Monojit Mitra
PIER C , 2008,
Abstract: In this paper we formalizes a new discrete time model of digital array based MIMO radar in which the combined effects of the transmit filter, physical MIMO multi-path channel fading, and receive filter. It has the same sampling period as that of the MIMO receiver. Apart from this, SNR value and target detection are different in compared to the continuous domain nature. Orthogonality is introduced using OSTBC (orthogonal space time coding) including interelement spacing at the transmitter is greater than the target beam width coverage. For space and temporal diversity we have considered distributed source model. and modulation schemes respectively. Frequency diversity is achieved using point IFFT ( = 32, 64, 256, 1024) at the base band. Thus, three dimensional analysis with respect to diversity and selective nature of fading channel in digital array based MIMO radar are now used for performance analysis based on probability of detection, symbol error rate, model error, power spectral density at the receiver and SNR value at the detector.
Augmented Lattice Reduction for MIMO decoding  [PDF]
Laura Luzzi,Ghaya Rekaya-Ben Othman,Jean-Claude Belfiore
Mathematics , 2010,
Abstract: Lattice reduction algorithms, such as the LLL algorithm, have been proposed as preprocessing tools in order to enhance the performance of suboptimal receivers in MIMO communications. In this paper we introduce a new kind of lattice reduction-aided decoding technique, called augmented lattice reduction, which recovers the transmitted vector directly from the change of basis matrix, and therefore doesn't entail the computation of the pseudo-inverse of the channel matrix or its QR decomposition. We prove that augmented lattice reduction attains the maximum receive diversity order of the channel; simulation results evidence that it significantly outperforms LLL-SIC detection without entailing any additional complexity. A theoretical bound on the complexity is also derived.
Envelope Correlation Parameter Measurements in a MIMO Antenna Array Configuration  [PDF]
Constantinos Votis, George Tatsis, Panos Kostarakis
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2010, DOI: 10.4236/ijcns.2010.34044
Abstract: In a 2 × 2 MIMO antenna array system envelope correlation coefficient “ρ” shows the influence of different propagation paths of the RF signals that reach the antenna elements. The approximated value of this coefficient is based on a simple closed-form equation and also varies from 0 to 1. Quite perfect performance for MIMO applications is achieved when this parameter approximates to zero. In this paper, we evaluate an antenna diversity MIMO system by measuring the envelope correlation coefficient. The corresponding results in our antenna array configurations show that the measured “ρ” has very small values and approximates to zero. This observation indicates quite perfect behavior and performance of our MIMO antenna array system.
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