Multisensor data fusion is an emerging technology applied to Department of Defense (DoD) areas such as automated target recognition, battlefield surveillance, and guidance and control of autonomous vehicles, and to non-DoD applications such as monitoring of complex machinery, medical diagnosis, and smart buildings. Techniques for multisensor data fusion are drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation and other areas. This paper provides a tutorial on data fusion, introducing data fusion applications, process models, and identification of applicable techniques. Comments are made on the state-of-the-art in data fusion.

An introduction to multisensor data fusion

A computationally efficient algorithm for parameter estimation of superimposed signals based on the two-step iterative EM (estimate-and-maximize, with an E step and an M step) algorithm is developed. The idea is to decompose the observed data into their signal components and then to estimate the parameters of each signal component separately. The algorithm iterates back and forth, using the current parameter estimates to decompose the observed data better and thus increase the likelihood of the next parameter estimates. The application of the algorithm to the multipath time delay and multiple-source location estimation problems is considered. >

/pdf/parameter-estimation-of-superimposed-signals-using-the-em-b1fg5f44tw.pdf

Parameter estimation of superimposed signals using the EM algorithm

A short historical overview of matched-field processing (MFP) is followed by background material in both ocean acoustics and array processing needed for MFP. Specific algorithms involving both quadratic and adaptive methods are then introduced. The results of mismatch studies and several algorithms designed to be relatively robust against mismatch are discussed. The use of simulated MFP for range, depth and bearing location is examined, using data from a towed array that has been tilted to produce an effective vertical aperture. Several experiments using MFP are reviewed. One successfully demonstrated MFP at megameter ranges; this has important consequences for experiments in global tomography. Some unique applications of MFP, including how it can exploit ocean inhomogeneities and make tomographic measurements of environmental parameters, are considered. >

An overview of matched field methods in ocean acoustics

Four fundamental limitations in antennas have been identified in the areas of: electrically small antennas, superdirective antennas, superresolution antennas, and high-pin antennas. All exhibit roughly exponential increase in cost factors with performance increase beyond the robust range. This paper reviews these limitations. Electrically small antennas are analyzed via spherical mode theory, with the antenna enclosed in a virtual sphere. Minimum Q varies inversely as the cube of sphere radius in radian wavelengths when the radius is much less than the latter. This limits the achievable bandwidth. Superdirective apertures require a constraint; the optimization is generally intractable except for line sources. Superdirective arrays have spacing below half-wavelength, and for small spacings a constraint is desirable to limit Q, tolerances, efficiency, sidelobes, etc. This is accomplished by expressing constrained directivity as a ratio of two Hermilian quadratic forms, for which a solution exists. Array Q varies exponentially with directivity so only modest increases are practical. Superresolution arrays use maximum entropy processes to improve spatial frequency resolution for short samples (short arrays), analogous to spectral analysis processing. An amplitude-tapered autocorrelation function is extended by linear least square prediction and autoregression; the latter contributes filter poles. This extension is with minimum added information, hence maximum entropy. In contrast to superdirective arrays which are all zero functions, superresolution maximum entropy uses an all pole function. Results are dependent upon the sampling subarray size and upon signal/noise (S/N). Required S/N increases exponentially with inverse angular resolution. Achievable gain of high-gain reflector antennas is limited by cost of the structure. For random surface errors maximum gain is proportional to the mechanical tolerance ratio (antenna diameter/1σ tolerance) squared. Since cost increases rapidly with diameter and with tolerance ratio this comprises a gain limitation. Current best reflectors have maximum gain in the range of 90 to 100 dB.

Fundamental limitations in antennas

The authors have developed a method suitable for reconstructing spatio-temporal activities of neural sources by using magnetoencephalogram (MEG) data. The method extends the adaptive beamformer technique originally proposed by Borgiotti and Kaplan (1979) to incorporate the vector beamformer formulation in which a set of three weight vectors are used to detect the source activity in three orthogonal directions. The weight vectors of the vector-extended version of the Borgiotti-Kaplan beamformer are then projected onto the signal subspace of the measurement covariance matrix to obtain the final form of the proposed beamformer's weight vectors. The authors' numerical experiments show that both spatial resolution and output signal-to-noise ratio of the proposed beamformer are significantly higher than those of the minimum-variance-based vector beamformer used in previous investigations. The authors also applied the proposed beam former to two sets of auditory-evoked MEG data, and the results clearly demonstrated the method's capability of reconstructing spatio-temporal activities of neural sources.

https://www.comp.sd.tmu.ac.jp/sekihara/pdfs/vector_ieee.pdf

Reconstructing spatio-temporal activities of neural sources using an MEG vector beamformer technique

By using adaptive techniques an antenna array can achieve an angular resolution of uncorrelated interference sources substantially greater than the aperture of diffraction limit. The antenna beam is scanned over the interference source locations, and for each scan condition the adaptive processor is allowed to reach its steady state. It is shown that for realistic ratios of interference strengths to system thermal noise, resolutions in excess of 0.25 times the Rayleigh limit can be achieved.

L. Kaplan

Papers

Superresolution of uncorrelated interference sources by using adaptive array techniques