B. S. Rao, H. F. Durrant-Whyte, “A decentralized Bayesian algorithm for identification of tracked targets,” IEEE Trans. Syst. Man Cybern. 23, 1683–1698 (1993).

[CrossRef]

D. Andrisani, E. T. Kim, J. Schierman, “A nonlinear helicopter tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. 27, 40–47 (1991).

[CrossRef]

B. Jeyendran, V. U. Reddy, “Recursive system identification in the presence of burst disturbance,” Signal Process. 20, 227–245 (1990).

[CrossRef]

D. Andrisani, F. P. Kuhl, D. Gleason, “A nonlinear tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. AES-22, 533–539 (1986).

[CrossRef]

B. J. Rye, “Power ratio estimation in incoherent backscatter LIDAR: heterodyne receiver with square law detection,” J. Climate Appl. Meteorol. 22, 1899–1913 (1983).

[CrossRef]

J. K. Tugnait, A. H. Haddad, “A detection estimation scheme for state estimation in switching environments,” Automatica 15, 477–481 (1979).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

H. Akashi, H. Kumamoto, “Random sampling approach to state estimation in switching environments,” Automatica 13, 429–434 (1977).

[CrossRef]

D. S. Zrnic, “Mean power estimation with a recursive filter,” IEEE Trans. Aerosp. Electron. Syst. AES-13, 281–289 (1977).

[CrossRef]

D. G. Lainiotis, “Partitioning: a unifying framework for adaptive systems, I: estimation,” Proc. IEEE 64, 1126–1143 (1976).

[CrossRef]

D. G. Lainiotis, “Partitioned estimation algorithms II: nonlinear estimation,” J. Inf. Sci. 7, 202–235 (1974).

D. G. Lainiotis, S. K. Park, “On joint detection, estimation and system identification: discrete data case,” Int. J. Control 17, 609–633 (1973).

[CrossRef]

D. G. Lainiotis, “Joint detection, estimation, and system identification,” Inf. Control J. 19, 75–92 (1971).

[CrossRef]

H. W. Sorenson, D. L. Alspach, “Recursive Bayesian estimation using Gaussian sums,” Automatica 7, 465–479 (1971).

[CrossRef]

D. G. Lainiotis, “Optimal adaptive estimation: structure and parameter adaptation,” IEEE Trans. Autom. Control AC-16, 160–170 (1971).

[CrossRef]

D. G. Lainiotis, “Optimal nonlinear estimation,” Int. J. Control 14, 1137–1148 (1971).

[CrossRef]

G. A. Ackerson, K. S. Fu, “On state estimation in switching environments,” IEEE Trans. Autom. Control AC-15, 10–17 (1970).

[CrossRef]

D. G. Lainiotis, “Sequential structure and parameter adaptive pattern recognition, part I: supervised learning,” IEEE Trans. Inf. Theory IT-16, 548–556 (1970).

[CrossRef]

H. W. Sorenson, A. R. Stubberud, “Nonlinear filtering by approximation of the A-posteriori density,” Int. J. Control 18, 33–51 (1968).

[CrossRef]

J. A. Nelder, R. Mead, “A simplex method for function minimization,” Comput. J. 7, 308–313 (1965).

R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82, 35–45 (1960).

[CrossRef]

G. A. Ackerson, K. S. Fu, “On state estimation in switching environments,” IEEE Trans. Autom. Control AC-15, 10–17 (1970).

[CrossRef]

H. Akashi, H. Kumamoto, “Random sampling approach to state estimation in switching environments,” Automatica 13, 429–434 (1977).

[CrossRef]

H. W. Sorenson, D. L. Alspach, “Recursive Bayesian estimation using Gaussian sums,” Automatica 7, 465–479 (1971).

[CrossRef]

D. Andrisani, E. T. Kim, J. Schierman, “A nonlinear helicopter tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. 27, 40–47 (1991).

[CrossRef]

D. Andrisani, F. P. Kuhl, D. Gleason, “A nonlinear tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. AES-22, 533–539 (1986).

[CrossRef]

J. V. Candy, Signal Processing: The Model-Based Approach (McGraw-Hill, New York, 1986).

B. S. Rao, H. F. Durrant-Whyte, “A decentralized Bayesian algorithm for identification of tracked targets,” IEEE Trans. Syst. Man Cybern. 23, 1683–1698 (1993).

[CrossRef]

G. A. Ackerson, K. S. Fu, “On state estimation in switching environments,” IEEE Trans. Autom. Control AC-15, 10–17 (1970).

[CrossRef]

D. Andrisani, F. P. Kuhl, D. Gleason, “A nonlinear tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. AES-22, 533–539 (1986).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

J. K. Tugnait, A. H. Haddad, “A detection estimation scheme for state estimation in switching environments,” Automatica 15, 477–481 (1979).

[CrossRef]

B. J. Rye, R. M. Hardesty, “Nonlinear Kalman filtering techniques for incoherent backscatter LIDAR: return power and log power estimation,” Appl. Opt. 28, 3908–3917 (1989).

[CrossRef]
[PubMed]

B. J. Rye, R. M. Hardesty, “Time series identification and Kalman filtering techniques for doppler LIDAR velocity estimation,” Appl. Opt. 28, 879–891 (1989).

[CrossRef]
[PubMed]

B. J. Rye, R. M. Hardesty, “Power estimator bias in filtered incoherent backscatter heterodyne LIDAR returns,” in Coherent Laser Radar, 1991 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1991), Poster paper.

B. Jeyendran, V. U. Reddy, “Recursive system identification in the presence of burst disturbance,” Signal Process. 20, 227–245 (1990).

[CrossRef]

R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82, 35–45 (1960).

[CrossRef]

D. Andrisani, E. T. Kim, J. Schierman, “A nonlinear helicopter tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. 27, 40–47 (1991).

[CrossRef]

D. Andrisani, F. P. Kuhl, D. Gleason, “A nonlinear tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. AES-22, 533–539 (1986).

[CrossRef]

H. Akashi, H. Kumamoto, “Random sampling approach to state estimation in switching environments,” Automatica 13, 429–434 (1977).

[CrossRef]

D. G. Lainiotis, “Partitioning: a unifying framework for adaptive systems, I: estimation,” Proc. IEEE 64, 1126–1143 (1976).

[CrossRef]

D. G. Lainiotis, “Partitioned estimation algorithms II: nonlinear estimation,” J. Inf. Sci. 7, 202–235 (1974).

D. G. Lainiotis, S. K. Park, “On joint detection, estimation and system identification: discrete data case,” Int. J. Control 17, 609–633 (1973).

[CrossRef]

D. G. Lainiotis, “Joint detection, estimation, and system identification,” Inf. Control J. 19, 75–92 (1971).

[CrossRef]

D. G. Lainiotis, “Optimal adaptive estimation: structure and parameter adaptation,” IEEE Trans. Autom. Control AC-16, 160–170 (1971).

[CrossRef]

D. G. Lainiotis, “Optimal nonlinear estimation,” Int. J. Control 14, 1137–1148 (1971).

[CrossRef]

D. G. Lainiotis, “Sequential structure and parameter adaptive pattern recognition, part I: supervised learning,” IEEE Trans. Inf. Theory IT-16, 548–556 (1970).

[CrossRef]

D. G. Lainiotis, “Adaptive pattern recognition: a state variable approach,” in Advances in Pattern Recognition, M. Watanabe, ed. (Academic, New York, 1972).

L. S. Segal, D. G. Lainiotis, “Partitioned adaptive estimation of time-varying random parameters with applications to economic forecasting,” in Proceedings of the Joint Automatic Control Conference, Denver, Colo. (1979), pp. 527–531.

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

J. A. Nelder, R. Mead, “A simplex method for function minimization,” Comput. J. 7, 308–313 (1965).

J. A. Nelder, R. Mead, “A simplex method for function minimization,” Comput. J. 7, 308–313 (1965).

D. G. Lainiotis, S. K. Park, “On joint detection, estimation and system identification: discrete data case,” Int. J. Control 17, 609–633 (1973).

[CrossRef]

B. S. Rao, H. F. Durrant-Whyte, “A decentralized Bayesian algorithm for identification of tracked targets,” IEEE Trans. Syst. Man Cybern. 23, 1683–1698 (1993).

[CrossRef]

B. Jeyendran, V. U. Reddy, “Recursive system identification in the presence of burst disturbance,” Signal Process. 20, 227–245 (1990).

[CrossRef]

B. J. Rye, R. M. Hardesty, “Nonlinear Kalman filtering techniques for incoherent backscatter LIDAR: return power and log power estimation,” Appl. Opt. 28, 3908–3917 (1989).

[CrossRef]
[PubMed]

B. J. Rye, R. M. Hardesty, “Time series identification and Kalman filtering techniques for doppler LIDAR velocity estimation,” Appl. Opt. 28, 879–891 (1989).

[CrossRef]
[PubMed]

B. J. Rye, “Power ratio estimation in incoherent backscatter LIDAR: heterodyne receiver with square law detection,” J. Climate Appl. Meteorol. 22, 1899–1913 (1983).

[CrossRef]

B. J. Rye, “A wavelength switching algorithm for single laser differential absorption LIDAR systems,” in Laser Applications in Meteorology and Earth Atmospheric Remote Sensing, M. M. Sokoloski, ed., Proc. SPIE 1062, 267–273 (1989).

B. J. Rye, “Kalman filtering in LIDAR,” in Proceedings of the Fifth Conference on Coherent Laser Radar, Munich, 1989.

B. J. Rye, R. M. Hardesty, “Power estimator bias in filtered incoherent backscatter heterodyne LIDAR returns,” in Coherent Laser Radar, 1991 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1991), Poster paper.

D. Andrisani, E. T. Kim, J. Schierman, “A nonlinear helicopter tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. 27, 40–47 (1991).

[CrossRef]

L. S. Segal, D. G. Lainiotis, “Partitioned adaptive estimation of time-varying random parameters with applications to economic forecasting,” in Proceedings of the Joint Automatic Control Conference, Denver, Colo. (1979), pp. 527–531.

H. W. Sorenson, D. L. Alspach, “Recursive Bayesian estimation using Gaussian sums,” Automatica 7, 465–479 (1971).

[CrossRef]

H. W. Sorenson, A. R. Stubberud, “Nonlinear filtering by approximation of the A-posteriori density,” Int. J. Control 18, 33–51 (1968).

[CrossRef]

H. W. Sorenson, A. R. Stubberud, “Nonlinear filtering by approximation of the A-posteriori density,” Int. J. Control 18, 33–51 (1968).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

J. K. Tugnait, “Detection and estimation for abruptly changing systems,” Automatica 18, 607–615 (1982).

[CrossRef]

J. K. Tugnait, A. H. Haddad, “A detection estimation scheme for state estimation in switching environments,” Automatica 15, 477–481 (1979).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

D. S. Zrnic, “Mean power estimation with a recursive filter,” IEEE Trans. Aerosp. Electron. Syst. AES-13, 281–289 (1977).

[CrossRef]

B. J. Rye, R. M. Hardesty, “Time series identification and Kalman filtering techniques for doppler LIDAR velocity estimation,” Appl. Opt. 28, 879–891 (1989).

[CrossRef]
[PubMed]

B. J. Rye, R. M. Hardesty, “Nonlinear Kalman filtering techniques for incoherent backscatter LIDAR: return power and log power estimation,” Appl. Opt. 28, 3908–3917 (1989).

[CrossRef]
[PubMed]

N. Menyuk, D. K. Killinger, C. R. Menyuk, “Limitations of signal averaging due to temporal correlation in laser remote sensing measurements,” Appl. Opt. 21, 3377–3383 (1982).

[CrossRef]
[PubMed]

W. B. Grant, A. M. Brothers, J. R. Bogan, “DIAL signal averaging,” Appl. Opt. 27, 1934–1938 (1988).

[CrossRef]
[PubMed]

M. J. T. Milton, P. T. Woods, “Pulse averaging methods for a laser remote monitoring system using atmospheric backscatter,” Appl. Opt. 26, 2598–2603 (1987).

[CrossRef]
[PubMed]

R. E. Warren, “Adaptive Kalman–Bucy filter for differential absorption LIDAR time series data,” Appl. Opt. 26, 4755–4760 (1987).

[CrossRef]
[PubMed]

D. Letalick, M. Millnert, I. Renhorn, “Terrain segmentation using laser radar range data,” Appl. Opt. 31, 2883–2890 (1992).

[CrossRef]
[PubMed]

H. Akashi, H. Kumamoto, “Random sampling approach to state estimation in switching environments,” Automatica 13, 429–434 (1977).

[CrossRef]

J. K. Tugnait, A. H. Haddad, “A detection estimation scheme for state estimation in switching environments,” Automatica 15, 477–481 (1979).

[CrossRef]

J. K. Tugnait, “Detection and estimation for abruptly changing systems,” Automatica 18, 607–615 (1982).

[CrossRef]

H. W. Sorenson, D. L. Alspach, “Recursive Bayesian estimation using Gaussian sums,” Automatica 7, 465–479 (1971).

[CrossRef]

J. A. Nelder, R. Mead, “A simplex method for function minimization,” Comput. J. 7, 308–313 (1965).

D. S. Zrnic, “Mean power estimation with a recursive filter,” IEEE Trans. Aerosp. Electron. Syst. AES-13, 281–289 (1977).

[CrossRef]

D. Andrisani, F. P. Kuhl, D. Gleason, “A nonlinear tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. AES-22, 533–539 (1986).

[CrossRef]

D. Andrisani, E. T. Kim, J. Schierman, “A nonlinear helicopter tracker using attitude measurements,” IEEE Trans. Aerosp. Electron. Syst. 27, 40–47 (1991).

[CrossRef]

D. G. Lainiotis, “Optimal adaptive estimation: structure and parameter adaptation,” IEEE Trans. Autom. Control AC-16, 160–170 (1971).

[CrossRef]

G. A. Ackerson, K. S. Fu, “On state estimation in switching environments,” IEEE Trans. Autom. Control AC-15, 10–17 (1970).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—I. Identification of persistent rhythms,” IEEE Trans. Biomed. Eng. BME-25, 344–353 (1978).

[CrossRef]

D. E. Gustafson, A. S. Willsky, J. Y. Wang, M. C. Lancaster, J. H. Triebwasser, “ECG/VCG rhythm diagnosis using statistical signal analysis—II. Identification of transient rhythms,” IEEE Trans. Biomed. Eng. BME-25, 353–361 (1978).

[CrossRef]

D. G. Lainiotis, “Sequential structure and parameter adaptive pattern recognition, part I: supervised learning,” IEEE Trans. Inf. Theory IT-16, 548–556 (1970).

[CrossRef]

B. S. Rao, H. F. Durrant-Whyte, “A decentralized Bayesian algorithm for identification of tracked targets,” IEEE Trans. Syst. Man Cybern. 23, 1683–1698 (1993).

[CrossRef]

D. G. Lainiotis, “Joint detection, estimation, and system identification,” Inf. Control J. 19, 75–92 (1971).

[CrossRef]

D. G. Lainiotis, “Optimal nonlinear estimation,” Int. J. Control 14, 1137–1148 (1971).

[CrossRef]

H. W. Sorenson, A. R. Stubberud, “Nonlinear filtering by approximation of the A-posteriori density,” Int. J. Control 18, 33–51 (1968).

[CrossRef]

D. G. Lainiotis, S. K. Park, “On joint detection, estimation and system identification: discrete data case,” Int. J. Control 17, 609–633 (1973).

[CrossRef]

R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng. 82, 35–45 (1960).

[CrossRef]

B. J. Rye, “Power ratio estimation in incoherent backscatter LIDAR: heterodyne receiver with square law detection,” J. Climate Appl. Meteorol. 22, 1899–1913 (1983).

[CrossRef]

D. G. Lainiotis, “Partitioned estimation algorithms II: nonlinear estimation,” J. Inf. Sci. 7, 202–235 (1974).

D. G. Lainiotis, “Partitioning: a unifying framework for adaptive systems, I: estimation,” Proc. IEEE 64, 1126–1143 (1976).

[CrossRef]

B. Jeyendran, V. U. Reddy, “Recursive system identification in the presence of burst disturbance,” Signal Process. 20, 227–245 (1990).

[CrossRef]

D. G. Lainiotis, “Adaptive pattern recognition: a state variable approach,” in Advances in Pattern Recognition, M. Watanabe, ed. (Academic, New York, 1972).

J. V. Candy, Signal Processing: The Model-Based Approach (McGraw-Hill, New York, 1986).

A. Gelb, ed., Applied Optimal Estimation (MIT, Cambridge, 1974).

B. J. Rye, “A wavelength switching algorithm for single laser differential absorption LIDAR systems,” in Laser Applications in Meteorology and Earth Atmospheric Remote Sensing, M. M. Sokoloski, ed., Proc. SPIE 1062, 267–273 (1989).

B. J. Rye, “Kalman filtering in LIDAR,” in Proceedings of the Fifth Conference on Coherent Laser Radar, Munich, 1989.

B. J. Rye, R. M. Hardesty, “Power estimator bias in filtered incoherent backscatter heterodyne LIDAR returns,” in Coherent Laser Radar, 1991 OSA Technical Digest Series (Optical Society of America, Washington, D.C., 1991), Poster paper.

L. S. Segal, D. G. Lainiotis, “Partitioned adaptive estimation of time-varying random parameters with applications to economic forecasting,” in Proceedings of the Joint Automatic Control Conference, Denver, Colo. (1979), pp. 527–531.