Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays

Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an essential task in sonar, radar, acoustics, biomedical and multimedia applications. Many state of the art wide-band DOA estimators coherently process frequency binned array outputs by approximate Maximum Likelihood, Weighted Subspace Fitting or focusing techniques. This paper shows that bin signals obtained by filter-bank approaches do not obey the finite rank narrow-band array model, because spectral leakage and the change of the array response with frequency within the bin create \emph{ghost sources} dependent on the particular realization of the source process. Therefore, existing DOA estimators based on binning cannot claim consistency even with the perfect knowledge of the array response. In this work, a more realistic array model with a finite length of the sensor impulse responses is assumed, which still has finite rank under a space-time formulation. It is shown that signal subspaces at arbitrary frequencies can be consistently recovered under mild conditions by applying MUSIC-type (ST-MUSIC) estimators to the dominant eigenvectors of the wide-band space-time sensor cross-correlation matrix. A novel Maximum Likelihood based ST-MUSIC subspace estimate is developed in order to recover consistency. The number of sources active at each frequency are estimated by Information Theoretic Criteria. The sample ST-MUSIC subspaces can be fed to any subspace fitting DOA estimator at single or multiple frequencies. Simulations confirm that the new technique clearly outperforms binning approaches at sufficiently high signal to noise ratio, when model mismatches exceed the noise floor.Comment: 15 pages, 10 figures. Accepted in a revised form by the IEEE Trans. on Signal Processing on 12 February 1918. @IEEE201

Multiple Signal Classification for Determining Direction of Arrival of Frequency Hopping Spread Spectrum Signals

This research extends a MUSIC algorithm to determine DOA of FHSS signals. All incident FHSS signals have unknown DOA and use PSK. Conventional MUSIC algorithm involves multiple MUSIC estimation for all frequency bins. On the other hand, the extended development is meant to execute a single MUSIC algorithm of observations on multiple frequency bins or hops. The new extension shows better performance compared to the conventional MUSIC execution at different SNR levels. Both have the same power accumulation at the true angles of arrival. However, the new development has lower side lobes and hence helps avoid false detections. In addition, the new development has lower side lobes variance resulting in lower error of false detections compared to the normal execution. Simulation results show that the new extension is sensitive to the SNR values and number of samples taken at each frequency bin. However, it is less sensitive to the possible number of frequency hops or hop set and number of array sensors

Signal Processing and Propagation for Aeroacoustic Sensor Networking,” Ch

Passive sensing of acoustic sources is attractive in many respects, including the relatively low signal bandwidth of sound waves, the loudness of most sources of interest, and the inherent difficulty of disguising or concealing emitted acoustic signals. The availability of inexpensive, low-power sensing and signal-processing hardware enables application of sophisticated real-time signal processing. Among th

Ultra wideband antenna array processing under spatial aliasing

Given a certain transmission frequency, Shannon spatial sampling limit de¯nes an upper bound for the antenna element spacing. Beyond this bound, the exceeded ambiguity avoids correct estimation of the signal parameters (i.e., array manifold crossing). This spacing limit is inversely proportional to the frequency of transmis- sion. Therefore, to meet a wider spectral support, the element spacing should be decreased. However, practical implementations of closely spaced elements result in a detrimental increase in electromagnetic mutual couplings among the sensors. Further- more, decreasing the spacing reduces the array angle resolution. In this dissertation, the problem of Direction of Arrival (DOA) estimation of broadband sources is ad- dressed when the element spacing of a Uniform Array Antenna (ULA) is inordinate. It is illustrated that one can resolve the aliasing ambiguity by utilizing the frequency diversity of the broadband sources. An algorithm, based on Maximum Likelihood Estimator (MLE), is proposed to estimate the transmitted data signal and the DOA of each source. In the sequel, a subspace-based algorithm is developed and the prob- lem of order estimation is discussed. The adopted signaling framework assumes a subband hopping transmission in order to resolve the problem of source associations and system identi¯cation. The proposed algorithms relax the stringent maximum element-spacing constraint of the arrays pertinent to the upper-bound of frequency transmission and suggest that, under some mild constraints, the element spacing can be conveniently increased. An approximate expression for the estimation error has also been developed to gauge the behavior of the proposed algorithms. Through con- ¯rmatory simulation, it is shown that the performance gain of the proposed setup is potentially signi¯cant, speci¯cally when the transmitters are closely spaced and under low Signal to Noise Ratio (SNR), which makes it applicable to license-free communication

Biological versus Subspace Methods in Sound Localization

Sound localization is determining the location of sound sources usingthe measurements of the signals received by an array ofsensors. Humans and animals possess the natural ability of localizingsound. Researchers have tried to model nature's way of solvingthis problem and have come up with different methods based on variousneuro-physiological studies. Such methods arecalled biological methods. On the other hand, there is another community ofresearchers who has looked at this problem from pure signalprocessing point of view. Among the more popular methods for solvingthis problem using signal processing techniques are the subspacemethods. In this thesis, a comparative study is done betweenbiological methods and subspace methods. Further, an attempt hasbeen made to incorporate the notion of head-related transfer functionin the modeling of subspace methods. The implementationof a biological localization algorithm on a DSP board is also presented

Direction of arrival estimation of WiMedia UWB multipath signals in the presence of inband interferers

Ph.DDOCTOR OF PHILOSOPH

Wide-band maximum likelihood direction finding by using the tree-structured EM algorithm

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1996.Thesis (Master's) -- Bilkent University, 1996.Includes bibliographical references leaves 38-43A thorough derivation of the Expectation Maximization (EM) algorithm, which is an iterative numerical method of Maximum Likelihood (ML) estimation, is presented for the case of estimating direction of arrivals of unknown deterministic wide-band signals incident from different directions onto a passive array. For the rec^uired signal estimation, alternative regularized least squares estimation techniques are proposed with significant improvement over the standard least squares techniques. Also, for the angle of arrival estimation of a large number of signals, a tree structured EM algorithm is proposed and compared with the conventional EM approach. Extensive simulation results are presented for comparison of the proposed algorithms with the current high-resolution methods of wide-band direction finding. In order to handle efficiently the case of available parametric prior models on the received waveforms, the required modifications are also given.Çadallı, NailM.S

High resolution space-time analysis by an active array

We present in this paper a high resolution method for the joint estimation of direction and time of arrival . This algorithm applies to active antenna for wich the emitted signal of some sources is known . After a brief recall of high resolution methods used in passive localization, we show how to introduce the knowledge of the signal in the MUSIC method . The proposed method is commented, particularly versus passive processing and active analysis of the signal received on one sensor. Performances of the method are then illustrated by simulation results .Nous présentons dans cet article une méthode haute résolution d'estimation conjointe de directions et de temps d'arrivée. Cet algorithme s'applique aux antennes actives pour lesquelles le signal émis par certaines sources est connu. Après un rappel des méthodes haute résolution utilisées en passif, nous montrons comment introduire la connaissance du signal dans la méthode MUSIC. La méthode proposée est commentée, notamment dans ses relations avec le traitement passif et avec l'analyse en actif du signal reçu sur un capteur unique. Les performances de la méthode sont ensuite illustrées par des résultats de simulatio