Architectural Acoustics: Acoustics of Concert Halls II

Some high-resolution direction-of-arrival DOA estimation methods, such as the MUSIC method, have been developed based on vectorsensor array. However, these high-resolution methods suffer from serious drawbacks. Indeed, they are not able to estimate coherent signals and sensitive to calibration errors. Mainly to overcome these limitations and in particular to satisfy practical engineering application, vector-sensor array beamforming based on fourth-order cumulants is adopted in this paper. The main interest in using fourth-order cumulants instead of second-order ones in vector-sensor array processing application is the aperture extension property of higher-order cumulants, which makes it possible to increase both the resolution and the number of sources to be processed from a given array, and suppress the Gaussian noise. Based on this method, smaller size of array and higher accuracy of DOA estimation can be realized, besides, this method is less sensitive to the coherence of the signals and calibration errors, which makes it possible to work well in engineering application. The results of computer simulation and analysis of data from outfield trials show that this method excels traditional direct estimation and can improve estimation capability of vector-sensor arrays. 2:20 2pSPa2. Robust array pattern synthesis with uncertain manifold vector. Shefeng Yan Department of Electronics and Telecommunications, Norwegian University of Science and Technology, O.S. Bragstads plass 2A, 7491 Trondheim, Norway, [email protected] The knowledge of the array manifold vectors of an acoustic array can be imprecise, which is often the case in practice. This may cause undesirably high sidelobes for a nominal optimal beamformer where the array manifold vectors are assumed to be known exactly. Although the norm constraint on beamformer weights can be imposed to improve the robustness of the optimal beamformer, it is not clear how to choose the optimal constrained parameter based on the known level of uncertainty of the array manifold vectors. A pattern synthesis approach to arbitrary arrays with robustness against array manifold vectors errors is developed. Our technique optimizes the worst-case performance by minimizing the worst-case sidelobe level while maintaining a distortionless response to the worst-case signal steering vector. The parameters can be optimally chosen based on the uncertainty of the array manifold vector. The robust beamformer problem is shown to be convex, which can be efficiently solved using second-order cone programming. A simple lower bound on how much worse the robust optimal beamformer will be compared to the nominal one is also derived. Computer simulations show better performance of the proposed robust beamformer. 2:40 2pSPa3. Analytical prediction of sample eigenvector quality deterioration in large arrays due to SNR or sample size constraints. Raj Nadakuditi MIT, Department of Mathematics, 77 Massachusetts Avenue, Cambridge, MA 02139, USA, [email protected] , Arthur B. Baggeroer MIT, Department of Mathematics, 77 Massachusetts Avenue, Cambridge, MA 02139, USA, [email protected] It is well-known that subspace-based estimation methods in adaptive array processing suffer a rapid degradation in performance as either the signalto-noise ratio SNR or the number of available snapshots drops below a certain threshold value. In the large system, relative large sample size limit, one can use random matrix theory to analytically predict this threshold and the degradation in the ’’quality’’ of the corresponding subspace estimates. In certain settings, one observes a phase transition phenonemon so that if the signals are too weak or there are insufficient number of snapshots or both, the subspace estimates are, statistically speaking, noise-like. We discuss the implication of these results for the subspace based detection of signals in white and colored noise using large arrays and illustrate the accuracy of the predictions with numerical simulations. 3:00 2pSPa4. Efficient Replica Generation for Space Time Adaptive Processing of Acoustic Signals. Neena Imam Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831-6015, USA, [email protected] , Jacob Barhen Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37831-6015, USA, [email protected] , Michael Traweek Office of Naval Research, 875 North Randolph Street, Arlington, VA 22203, USA, Mike.Traweek@navy .mil This paper addresses an innovative method for real-time replica generation using generalized Green’s function for Space Time Adaptive Processing STAP technology for sonar applications. In hypothesis processing for STAP algorithms, the first step is to generate replicas for various target hypothesis such as the infinite-range fixed-direction IRFD target hypotheses or the tracking trajectory hypotheses. Once generated, these replicas are used in multiple steps of the STAP algorithm for computing system parameters such as the signal to noise ratio. Replicas are traditionally precomputed or hard-wired due to computational load constraints. Such a precomputation precludes direct application of array shape corrections, and limits the ability to process arbitrary target trajectories. W propose to use a generalized Green’s function for efficient and ultra-fast real-time generation of replicas on multi-core processors Specifically, for an arbitrary target trajectory rT ti xT ti , yT ti , zT ti , arbitrary receive array trajectory rR k ti xR k ti , yR k ti , zR k ti , k 1,...,NEL , arbitrary vector of frequencies in homogeneous acoustic medium f f1,f2,....,fn,... , and sound speed c0, we can write G rT ti ,rR k ti ,fn c0 exp j 2 fn”c0 rR k ti rT ti ” rR k ti rT ti In terms of rationale, this is the simplest possible replica set for any STAP algorithm. The efficient implementation of the generalized Green’s function on a multi-core processor will allow real-time adjustment”modification of acoustical target tracking resulting in improved numerical accuracy and time performance. 3334 3334 J. Acoust. Soc. Am., Vol. 123, No. 5, Pt. 2, May 2008 Acoustics’08 Paris Downloaded 09 Jul 2012 to 131.174.209.225. Redistribution subject to ASA license or copyright; see http://asadl.org/journals/doc/ASALIB-home/info/terms.jsp 3:20 2pSPa5. Beam-forming with progressive focalisation. Gaetano Caronna Università La Sapienza Dept. Fisica Tecnica, Via Eudossiana 18, 00184 Roma, Italy, [email protected] , Pierluigi Testa Università La Sapienza Dept. Fisica Tecnica, Via Eudossiana 18, 00184 Roma, Italy, [email protected] This investigation is aiming to detect and track a moving target using its acoustic emissions and applying a new beam-forming approach. An original algorithm of medium computational complexity is reported that is capable of locating, with good accuracy, the direction of an acoustic source with only a few microphones. This algorithm circumvents the known localisation ambiguities due to the unwanted grating lobes , by using all spectral content of the acoustic source and progressively and narrowly focusing its beam in the direction of the target. The algorithm starts by locating the direction of the target with low angular resolution, using only low frequency components of the acoustic emissions; in this way, no grating lobes occur even with only a few microphones. Then, the angular resolution is increased by processing higher frequencies of the spectrum, but profiting of the information on the angular position achieved in the previous stages. Some algorithmic means are introduced to increase the performance of the algorithmic against environmental noise. This scheme is described in detail. Some experimental tests are included and discussed. TUESDAY AFTERNOON, 1 JULY 2008 P3-C, LEVEL 3, 3:40 TO 5:20 P.M.