An introduction to multisensor data fusion

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.

[1]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[2]  P. Sneath,et al.  Numerical Taxonomy , 1962, Nature.

[3]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[4]  Lotfi A. Zadeh,et al.  Fuzzy Algorithms , 1968, Inf. Control..

[5]  J. Capon.  High-resolution frequency-wavenumber spectrum analysis , 1969 .

[6]  H. Sorenson.  Least-squares estimation: from Gauss to Kalman , 1970, IEEE Spectrum.

[7]  P. R. Escobal,et al.  Methods of orbit determination , 1976 .

[8]  A. J. Cole,et al.  An Improved Algorithm for the Jardine-Sibson Method of Generating Overlapping Clusters , 1970, Computer/law journal.

[9]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise , 1992 .

[10]  Charles T. Zahn,et al.  Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters , 1971, IEEE Transactions on Computers.

[11]  Elijah Polak,et al.  Computational methods in optimization , 1971 .

[12]  J. Burg.  THE RELATIONSHIP BETWEEN MAXIMUM ENTROPY SPECTRA AND MAXIMUM LIKELIHOOD SPECTRA , 1972 .

[13]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[14]  V. Pisarenko.  The Retrieval of Harmonics from a Covariance Function , 1973 .

[15]  Y. Bar-Shalom,et al.  Tracking in a cluttered environment with probabilistic data association , 1975, Autom..

[16]  Josef Kittler,et al.  Mathematics Methods of Feature Selection in Pattern Recognition , 1975, Int. J. Man Mach. Stud..

[17]  Ramon E. Henkel.  Tests of Significance , 1976 .

[18]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[19]  J. Cappellari,et al.  Mathematical theory of the Goddard trajectory determination system , 1976 .

[20]  A.H. Haddad,et al.  Applied optimal estimation , 1976, Proceedings of the IEEE.

[21]  Keh-Ping Dunn,et al.  Kalman Filter Configurations for Multiple Radar Systems , 1976 .

[22]  G. Bierman.  Factorization methods for discrete sequential estimation , 1977 .

[23]  Keinosuke Fukunaga,et al.  A Branch and Bound Algorithm for Feature Subset Selection , 1977, IEEE Transactions on Computers.

[24]  Anil K. Jain,et al.  On the optimal number of features in the classification of multivariate Gaussian data , 1978, Pattern Recognit..

[25]  H. Skinner.  Dimensions and Clusters: A Hybrid Approach to Classification , 1979 .

[26]  S.S. Reddi,et al.  Multiple Source Location-A Digital Approach , 1979, IEEE Transactions on Aerospace and Electronic Systems.

[27]  S. Waligora,et al.  Orbit/attitude estimation with LANDSAT Landmark data , 1979 .

[28]  G. Borgiotti,et al.  Superresolution of uncorrelated interference sources by using adaptive array techniques , 1979 .

[29]  Anil K. Jain,et al.  Clustering Methodologies in Exploratory Data Analysis , 1980, Adv. Comput..

[30]  Yaakov Bar-Shalom,et al.  Multi-target tracking using joint probabilistic data association , 1980, 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[31]  Ralph Otto Schmidt,et al.  A signal subspace approach to multiple emitter location and spectral estimation , 1981 .

[32]  J. D. Lowrance,et al.  Evidential reasoning: a developing concept , 1982 .

[33]  Arthur Jay Barabell,et al.  Improving the resolution performance of eigenstructure-based direction-finding algorithms , 1983, ICASSP.

[34]  Brian Parker,et al.  Quantitative Applications in the Social Sciences , 1983 .

[35]  R. Kumaresan,et al.  Estimating the Angles of Arrival of Multiple Plane Waves , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[36]  W. Burdic.  Underwater Acoustic System Analysis , 1984 .

[37]  Gudmund R. Iversen,et al.  Bayesian statistical inference , 1984 .

[38]  M. Aldenderfer,et al.  Cluster Analysis. Sage University Paper Series On Quantitative Applications in the Social Sciences 07-044 , 1984 .

[39]  Hung T. Nguyen,et al.  Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty , 1985 .

[40]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[41]  Peter Jackson,et al.  Introduction to expert systems , 1986 .

[42]  Samuel S. Blackman,et al.  Multiple-Target Tracking with Radar Applications , 1986 .

[43]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[44]  G. B. Wilson.  Some aspects of data fusion , 1987 .

[45]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .

[46]  Peter C. Fishburn,et al.  Nonlinear preference and utility theory , 1988 .

[47]  Bernard Widrow,et al.  Neural nets for adaptive filtering and adaptive pattern recognition , 1988, Computer.

[48]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[49]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[50]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[51]  James Llinas,et al.  Data fusion technology forecast for C/sup 3/MIS , 1989 .

[52]  Michael D. Zoltowski,et al.  Sensor array signal processing via a procrustes rotations based eigenanalysis of the ESPRIT data pencil , 1989, IEEE Trans. Acoust. Speech Signal Process..

[53]  James Llinas,et al.  Multisensor Data Fusion , 1990 .

[54]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[55]  Keinosuke Fukunaga,et al.  Introduction to statistical pattern recognition (2nd ed.) , 1990 .

[56]  Thomas M. Sammon.  THE TRANSIENT EXPERT PROCESSOR , 1990, 1990 Conference Record Twenty-Fourth Asilomar Conference on Signals, Systems and Computers, 1990..

[57]  Stelios C. A. Thomopoulos.  Theories in distributed decision fusion: comparison and generalization , 1991, Other Conferences.

[58]  I. Goodman.  A General Theory for the Fusion of Data , 1991 .

[59]  James Llinas,et al.  Survey of multisensor data fusion systems , 1991, Defense, Security, and Sensing.

[60]  Yaakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking: Applications and Advances , 1992 .

[61]  Mongi A. Abidi,et al.  Data fusion in robotics and machine intelligence , 1992 .

[62]  D. L. Hall,et al.  Mathematical Techniques in Multisensor Data Fusion , 1992 .

[63]  Lawrence A. Klein,et al.  Sensor and Data Fusion Concepts and Applications , 1993 .

[64]  David A. Landgrebe,et al.  Decision boundary feature extraction for nonparametric classification , 1993, IEEE Trans. Syst. Man Cybern..

[65]  D.R. Hush,et al.  Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.

[66]  W. D. Blair,et al.  Tracking maneuvering targets with multiple, intermittent sensors , 1993, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers.

[67]  N. Bose,et al.  Neural network design using Voronoi diagrams , 1993, IEEE Trans. Neural Networks.

[68]  D. L. Hall,et al.  Survey of commercial software for multisensor data fusion , 1993, Defense, Security, and Sensing.

[69]  T. Kailath,et al.  A state-space approach to adaptive RLS filtering , 1994, IEEE Signal Processing Magazine.

[70]  A. Weigend,et al.  Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .

[71]  S.C.A. Thomopoulos,et al.  Sensor selectivity and intelligent data fusion , 1994, Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems.

[72]  L. G. Weiss.  Wideband processing of acoustic signals using wavelet transforms. Part II. Efficient implementation and examples , 1994 .

[73]  A. K. Garga,et al.  A neural network approach to the construction of Delaunay tessellation of points in R/sup d/ , 1994 .

[74]  Roy L. Streit,et al.  Maximum likelihood training of probabilistic neural networks , 1994, IEEE Trans. Neural Networks.

[75]  Roy L. Streit,et al.  Maximum likelihood method for probabilistic multihypothesis tracking , 1994, Defense, Security, and Sensing.

[76]  J. A. Stover,et al.  An autonomous fuzzy logic architecture for multisensor data fusion , 1994, Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems.

[77]  Andreas S. Weigend,et al.  Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .

[78]  S. G. Greineder,et al.  Procrustes: A Feature Set Reduction Technique , 1994 .

[79]  P. A. Delaney,et al.  A bibliography of higher-order spectra and cumulants , 1994 .

[80]  Aubrey B. Poore,et al.  A Numerical Study of Some Data Association Problems Arising in Multitarget Tracking , 1994 .

[81]  John Durkin,et al.  Expert systems - design and development , 1994 .

[82]  L. G. Weiss.  Wavelets and wideband correlation processing , 1994, IEEE Signal Processing Magazine.

[83]  Aubrey B. Poore,et al.  Multidimensional assignment formulation of data association problems arising from multitarget and multisensor tracking , 1994, Comput. Optim. Appl..

[84]  T. Söderström,et al.  On a Novel Subspace-Based Approach to Parameter Estimation , 1995 .

[85]  D. L. Hall,et al.  A new approach to the challenge of machinery prognostics , 1995 .

[86]  M. Kotanchek.  Stability Exploitation and Subspace Array Processing. , 1996 .