Ming Bao

DOA Estimation for Sparse Array via Sparse Signal Reconstruction

The problem of direction-of-arrival (DOA) estimation for sparse array is addressed. The perspective that DOA estimation in virtual array response model can be cast as the problem of sparse recovery is introduced. Two methods are proposed, based on different optimization problems, which are solvable using second-order cone (SOC) programming. Without the knowledge of the number of sources, the proposed methods yield superior performances, which are verified by numerical simulations.

Experimental demonstration of anomalous Floquet topological insulator for sound

Time reversal (T) invariant topological insulator is widely recognized as one of the fundamental discoveries in condensed matter physics, for which the most fascinating hallmark is perhaps a spin based topological protection, the total cancellation of scattering of conduction electrons with certain spins on matter surface. Recently, it has created a paradigm shift for topological insulators, from electronics to photonics, phononics as well as mechanics, bringing about not only involved new physics but also potential applications in robust wave transport. Despite the growing interests in realizing topologically protected acoustic wave transport, T-invariant acoustic topological insulator has not yet been achieved. Here, we report the first demonstration of acoustic topological insulator: a strongly coupled metamaterial ring lattice that supports one-way propagation of helical edge states under T-symmetry, backscattering immune to boundary abrupt variations. The very unique thing is the formation of spin-filtered interface states due to lattice dislocations. The mechanism underlying the formation of topologically protected edge states and interface states is applicable in various other wave systems or higher dimensions.Time-reversal invariant topological insulator is widely recognized as one of the fundamental discoveries in condensed matter physics, for which the most fascinating hallmark is perhaps a spin-based topological protection, the absence of scattering of conduction electrons with certain spins on matter surface. Recently, it has created a paradigm shift for topological insulators, from electronics to photonics, phononics and mechanics as well, bringing about not only involved new physics but also potential applications in robust wave transport. Despite the growing interests in topologically protected acoustic wave transport, T-invariant acoustic topological insulator has not yet been achieved. Here we report experimental demonstration of anomalous Floquet topological insulator for sound: a strongly coupled metamaterial ring lattice that supports one-way propagation of pseudo-spin-dependent edge states under T-symmetry. We also demonstrate the formation of pseudo-spin-dependent interface states due to lattice dislocations and investigate the properties of pass band and band gap states.

Subwavelength imaging through spoof surface acoustic waves on a two-dimensional structured rigid surface

We demonstrate that acoustic subwavelength imaging can be realized through the spoof surface acoustic waves on the surface phononic crystal which is composed of borehole arrays with square lattice in a rigid plate. The dispersion property of the spoof surface acoustic waves on the two-dimensional textured rigid plate is analyzed theoretically. By utilizing the broad flat equifrequency contour of the spoof surface acoustic waves, a subwavelength image with full width at half maximum of 0.14 λ has been obtained both numerically and experimentally. We believe that such work can bring potential applications in the design of acoustic imaging and focusing devices.

Fast communication: A novel wideband DOA estimator based on Khatri-Rao subspace approach

A novel DOA estimation method for uncorrelated wideband sources named focusing Khatri-Rao subspace method (FKR) is proposed based on coherent signal-subspace method (CSM) and Khatri-Rao (KR) subspace. Compared with the conventional CSM that simply averages the covariance matrices of different frequency bins after focusing, FKR transforms the covariance matrices into a higher dimensional matrix through KR product. This method has three major advantages: (1) it achieves a higher resolution than CSM, (2) the root mean square error of DOA estimation from FKR is smaller than that of CSM when the initial angles are inaccurate and (3) it performs well even when the number of sensors is reduced to about half of the sources. The performance of the FKR method is demonstrated and analyzed through the computer simulations.

Spatial separation of spoof surface acoustic waves on the graded groove grating

In this paper, a rigid surface decorated with an array of grooves with graded widths is proposed to get spatial separation of the spoof surface acoustic waves. Because of the intermodal coupling between forward and backward modes on the graded structure, the spoof surface acoustic waves with different frequencies stop propagating ahead and reflect back at different positions of the graded groove grating. The intensity of acoustic field is effectively enhanced near the propagation-stop position due to the slow group velocity. We believe that such system with the capability of energy concentration and wave spatial arrangement by frequencies has potential applications in acoustic wave coupling and absorption.

Generalized Iterated Kalman Filter and its Performance Evaluation

In this paper, we present a generalized iterated Kalman filter (GIKF) algorithm for state estimation of a nonlinear stochastic discrete-time system with state-dependent multiplicative observation noise. The GIKF algorithm adopts the Newton-Raphson iterative optimization steps to yield an approximate maximum a posteriori estimate of the states. The mean-square estimation error (MSE) and the Cramér-Rao lower bound (CRLB) of the state estimates are also derived. In particular, the local convergence of MSE of GIKF is rigorously established. It is also proved that the GIKF yields a smaller MSE than those of the generalized extended Kalman filter and the traditional extended Kalman filter. The performance advantages and convergence of GIKF are demonstrated using Monte Carlo simulations on a target tracking application in a range measuring sensor network.

The estimate for DOAs of signals using sparse recovery method

This paper presents a new direction-of-arrival (DOA) estimation method using the concept of sparse representation of an array cross-correlation vector (ACCV), in which DOA estimation is achieved by finding the sparse parameter vector according to an optimization criterion. Compared with other sparse recovery algorithms the proposed method achieves a higher resolution and has a less computational complexity. The performance of our method is demonstrated and analyzed through numerical simulations.

Experiments for on-line bearing-only target localization in acoustic array sensor networks

In this paper, we present a bearing-only on-line target localization platform, and succeed to realize the whole process of target localization. In the experiment, five nodes are used to send their moving target bearing line data to a base station which adopts asynchronous pseudolinear (APL) estimator for localization. The performance of Direction-of-arrival (DOA) estimation is analyzed in both cases of static and moving target. The results show on-line single target localization is satisfying.

Energy Balanced Scheduling for Target Tracking with Distance-Dependent Measurement Noise in a WSN

Energy efficient collaborative target tracking in a wireless sensor network (WSN) is considered. It is assumed that the distance estimates of range sensors are contaminated by distance-dependent multiplicative observation noises. The nonlinear measurement model leads to the application of a generalized unscented Kalman filtering (GUKF) tracking algorithm. Energy efficient operation is achieved by imposing an energy balance criterion to select a subset of sensors near the target to participate in collaborative tracking without compromising tracking performance. This is formulated as a multiobjective constrained optimization problem that minimizes both the state covariance of the GUKF algorithm and the variance of on-board residue energy of sensor nodes within the detection range of the target. An efficient, distributed, polynomial time heuristic algorithm that achieves a performance close to the optimal solution is proposed. Extended simulation results indicate that this proposed joint scheduling and tracking algorithm is capable of delivering desired tracking performance while significantly extending the WSN lifespan.

DOA Estimation From One-Bit Compressed Array Data via Joint Sparse Representation

A one-bit joint sparse representation direction of arrival (OBJSR-DOA) estimation approach is proposed in this letter. By exploiting the joint spatial and spectral correlations inherent in acoustic sensor array data, the proposed OBJSR-DOA approach provides reliable DOA estimation from only the sign bit of randomly subsampled acoustic sensor data. The random subsampling and single-bit quantization allow significant reduction of data to be transmitted to the fusion center without additional energy consumption requirement in the source coding/compression operation. Compared with existing compressive sensing-based DOA estimation methods, the superiority of the proposed approach in providing data volume reduction and performance improvement is verified by both simulations and field experiments using a prototype wireless sensor array network platform.