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ABSTRACT: In this paper, we present new adaptive and robust methods of reconstruction (ARMOR) for thermoacoustic tomography (TAT), and study their performances for breast cancer detection. TAT is an emerging medical imaging technique that combines the merits of high contrast due to electromagnetic or laser stimulation and high resolution offered by thermal acoustic imaging. The current image reconstruction methods used for TAT, such as the delay-and-sum (DAS) approach, are data-independent and suffer from low-resolution, high sidelobe levels, and poor interference rejection capabilities. The data-adaptive ARMOR can have much better resolution and much better interference rejection capabilities than their data-independent counterparts. By allowing certain uncertainties, ARMOR can be used to mitigate the amplitude and phase distortion problems encountered in TAT. The excellent performance of ARMOR is demonstrated using both simulated and experimentally measured data.
IEEE transactions on bio-medical engineering 01/2009; 55(12):2741-52. · 2.15 Impact Factor
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ABSTRACT: We present new beampattern synthesis approaches based on semidefinite relaxation (SDR) for signal power estimation. The conventional approaches use weight vectors at the array output for beampattern synthesis, which we refer to as the vector approaches (VA). Instead of this, we use weight matrices at the array output, which leads to matrix approaches (MA). We consider several versions of MA, including a (data) adaptive MA (AMA), as well as several data-independent MA designs. For all of these MA designs, globally optimal solutions can be determined efficiently due to the convex optimization formulations obtained by SDR. Numerical examples as well as theoretical evidence are presented to show that the optimal weight matrix obtained via SDR has few dominant eigenvalues, and often only one. When the number of dominant eigenvalues of the optimal weight matrix is equal to one, MA reduces to VA, and the main advantage offered by SDR in this case is to determine the globally optimal solution efficiently. Moreover, we show that the AMA allows for strict control of main-beam shape and peak sidelobe level while retaining the capability of adaptively nulling strong interferences and jammers. Numerical examples are also used to demonstrate that better beampattern designs can be achieved via the data-independent MA than via its VA counterpart.
IEEE Transactions on Signal Processing 01/2008; · 2.63 Impact Factor
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ABSTRACT: We consider multi-input multi-output (MIMO) transmit beamforming under the uniform elemental power constraint. This is a non-convex optimization problem, and it is usually difficult to find the optimal transmit beamformer. First, we show that for the multi-input single-output (MISO) case, the optimal solution has a closed-form expression. Then we propose a cyclic algorithm for the MIMO case which uses the closed- form MISO optimal solution iteratively. The cyclic algorithm has a low computational complexity and is locally convergent under mild conditions. Moreover, we consider finite-rate feedback methods needed for transmit beamforming. We propose a novel vector quantization method, where the codebook is constructed under the uniform elemental power constraint and the method is referred as VQ-UEP. Numerical examples are provided to demonstrate the effectiveness of our proposed transmit beamformer designs and the finite-rate feedback technique.
Signal Processing Advances in Wireless Communications, 2007. SPAWC 2007. IEEE 8th Workshop on; 07/2007
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ABSTRACT: We present new array beampattern synthesis approaches via semidefinite relaxation (SDR) for arbitrary array. Compared to the conventional approaches of using weight vectors at the array output for array pattern synthesis, which we refer to as the vector weighting approaches (VWA), weight matrices are used at the array output by MWA for much improved flexibility for optimal array pattern synthesis, and globally optimal solutions can be determined efficiently due to convex optimization formulations. Numerical examples are presented to show the excellent performance of MWA.
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on; 05/2007 · 4.63 Impact Factor
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ABSTRACT: We present the Adaptive WEighting of Signals via One Matrix Entity (AWESOME) algorithm for adaptive array beampattern synthesis. The array geometry can be arbitrary. Compared to the conventional approaches of using data-adaptive weight vectors at the array output for beampattern synthesis, which we refer to as the Vector Weighting Approaches (VWA), weight matrices are used at the array output by AWESOME for much improved flexibility for adaptive array beampattern synthesis. Globally optimal solutions can be determined efficiently for AWESOME due to the convex optimization formulations. AWESOME can be considered as the Semidefinite Relaxation (SDR) of the VWA counterpart. Numerical examples are presented to show that AWESOME allows for strict controls of main-beam shape and peak sidelobe level while retaining the capability of adaptive nulling of strong interferences and jammers.
Radar Conference, 2007 IEEE; 05/2007
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IEEE Transactions on Signal Processing. 01/2007; 55:5395-5406.
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IEEE Transactions on Signal Processing. 01/2007; 55:5643-5657.
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IEEE Transactions on Signal Processing. 01/2007; 55:4151-4161.
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ABSTRACT: Consider a vector moving-average sequence of order n, MA(n), and let denote its spectral density matrix, where are the covariance matrices and [omega] stands for the frequency variable. A nonparametric estimate of [Phi]([omega]) can easily become indefinite at some frequencies, and thus invalid, due to the estimation errors. In this paper, we provide a computationally efficient procedure that obtains the optimal (in a least-squares sense) valid approximation [Phi]([omega]) to in a polynomial time, by means of a semidefinite programming (SDP) algorithm.
Statistics [?] Probability Letters 01/2007; 77(10):973-980. · 0.50 Impact Factor
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ABSTRACT: We present two improved multi-static adaptive microwave imaging (MAMI) methods: MAMI-2 and MAMI-C, for early breast cancer detection. MAMI is one of the microwave imaging modalities based the significant contrast between the dielectric properties of normal and malignant breast tissues and employs multiple antennas that take turns to transmit ultra wideband (UWB) pulses while all antennas are used to receive the reflected signals. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite difference time domain (FDTD) method based on a 3-D realistic breast model
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on; 06/2006 · 4.63 Impact Factor
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Signals, Systems and Computers, 2005. Conference Record of the Thirty-Ninth Asilomar Conference on;
