Download or read book Using Multiple Model Adaptive Tracking of Airborne Targets written by John E. Norton (CAPT, USAF.) and published by . This book was released on 1988 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiple Model Adaptive Tracking of Airborne Targets written by John E. Norton and published by . This book was released on 1988 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past ten years considerable work has been accomplished at the Air Force Institute of Technology (AFIT) towards improving the ability of tracking airborne targets. Motivated by the performance advantages in using established models of tracking environment variables within a Kalman filter, an advanced tracking algorithm has been developed based on adaptive estimation filter structures. A multiple model bank of filters that have been designed for various target dynamics, which each accounting for atmospheric disturbance of the Forward Looking Infrared (FLIR) sensor data and mechanical vibrations of the sensor platform, outperforms a correlator tracker. The bank of filters provide the estimation capability to guide the pointing mechanisms of a shared aperture laser/sensor system. The data is provided to the tracking algorithm via an (8 x 8)-pixel tracking Field of View (FOV) from the FLIR image plane. Data at each sample period is compared by an enhanced correlator to a target template. These offsets are measurements to a bank of linear Kalman filters which provide estimates of the target's location in azimuth and elevation coordinates based on a Gauss-Markov acceleration model, and a reduced form of the atmospheric jitter model for the disturbance in the IR wavefront carrying future measurements. Theses. (RH).

Download or read book A Multiple Model Adaptive Tracking Algorithm Against Airborne Targets written by Thomas A. Leeney (CAPT, USAF.) and published by . This book was released on 1987 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Multiple Model Adaptive Tracking Algorithm Against Airborne Targets written by Thomas A. Leeney and published by . This book was released on 1987 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis extends the AFIT research directed towards replacing a standard correlation tracker with a Kalman filter bank/enhanced correlation tracker in a high energy laser weapon system. Airborne targets are tracked by a Bayesian multiple model adaptive filtering (MMAF) algorithm, which utilizes an array of infrared sensing detectors as the measurement information for two-dimensional position data. Two different target dynamics models are exercised: a linear, Gauss-Markov acceleration model, and a nonlinear, constant turn-rate model. Performance analyses are accomplished via Monte Carlo simulation techniques. Extending the adaptive potential of the tracking algorithm is of primary emphasis. The effects of bending and vibration of a large space structure on the FLIR's ability to resolve target position is analyzed. Also, a performance comparison/simulation time tradeoff is conducted with the tracking algorithm operating at both 30 Hz and 50 Hz. Sensitivity studies of adaptive responsiveness to varying target trajectories, various filter-assumed correlation times, range to pixel size relationships, and pixel size to filter driving white noise strength relationships are performed. The robustness of the multiple model algorithm is demonstrated by its ability to adapt to scenarios which it had not been previously tuned.

Download or read book Characteristics of Bayesian Multiple Model Adaptive Estimation for Tracking Airborne Targets written by Allan S. Netzer (CAPT, USAF.) and published by . This book was released on 1985 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhanced Tracking of Airborne Targets Using Multiple Model Filtering Techniques for Adaptive Field of View Expansion written by Robert I. Suizu (1LT, USAF.) and published by . This book was released on 1983 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhanced Tracking of Airborne Targets Using Multiple Model Filtering Techniques for Adaptive Field of View Expansion written by R. I. Suizu and published by . This book was released on 1983 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study was part of an ongoing effort at the Air Force Institute of Technology to design a tracking algorithm for use with the Air Force Weapons Laboratory's high energy laser weapon system. The purpose of this thesis was to take previously developed tracker algorithms and incorporate a multiple model adaptive filter algorithm into the existing structure. This approach was intended to provide adaptive expansion of the effective tracker field of view, which in turn would increase the tracker's ability to maintain lock on highly dynamic, close range targets.

Download or read book Bayesian Vs MAP Multiple Model Adaptive Estimation for Field of View Expansion in Tracking Airborne Targets written by Phyllis A. Loving (CAPT, USAF.) and published by . This book was released on 1985 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Characteristics of Bayesian Multiple Model Adaptive Estimation for Tracking Airborne Targets written by Allan S. Netzer and published by . This book was released on 1985 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Previous studies at the Air Force Institute of Technology have led to the development of a multiple model adaptive filter (MMAF) tracking algorithm which provides significant improvements in tracker performance against highly-dynamic airborne targets over the currently used correlation trackers. A forward looking infra-red (FLIR) sensor is used to provide a target shape function to the tracking algorithm in the form of an 8 x 8 array of intensities projected onto a field of view (FOV). This target image measurement is correlated with an estimate of the target image a template, to produce linear offset pseudo-measurements from the center of the FOV, which are provided as measurements to a bank of linear Kalman filters, in the multiple model adaptive filtering (MMAF) structure. The output of the MMAF provides the state estimates used in pointing the FLIR sensor, and generating the new target image estimate. This study investigates the characteristics of this algorithm in order to evaluate its performance against various target scenarios. (Author).

Download or read book Control and Dynamic Systems V31 Advances in Aerospace Systems Dynamics and Control Systems Part 1 of 3 written by C.T. Leonides and published by Elsevier. This book was released on 2012-12-02 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control and Dynamic Systems: Advances in Theory in Applications, Volume 31: Advances in Aerospace Systems Dynamics and Control Systems, Part 1 of 3 deals with significant advances in technologies which support the development of aerospace systems. It also presents several algorithms and computational techniques used in complex aerospace systems. The techniques discussed in this volume include: moving-bank multiple model adaptive estimation, algorithms for multitarget sensor tracking systems; algorithms in differential dynamic programming; optimal control of linear stochastic systems; and normalized predictive deconvulation. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.

Download or read book A Multiple Model Adaptive Tracking Algorithm for a High Energy Laser Weapon System written by David M. Tobin and published by . This book was released on 1986 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers replacing a standard correlation tracker with a hybrid Kalman filter/enhanced correlation tracker in a high energy laser weapon system. Dynamic airborne targets are tracked by a Bayesian multiple model adaptive filtering (MMAF) algorithm, which processes the outputs of a matrix-type array of infrared sensing detectors. Emphasis is placed on extending the adaptive potential of the tracking algorithm. This is accomplished by processing measurements from various field of view (FOV) sizes and shapes, and by incorporating direction-dependent target dynamics in some of the elemental Kalman filters within the multiple model structure. A sensor to target range tuning algorithm is derived which can be used for on line adaptive filter tuning should the tracker be provided range information, (even at low sample rates and/or precision), possibly via laser ranging. Also, the problem of initial target acquisition is explored through an algorithm which acquires the target in the center of the FOV despite initial sensor pointing errors. Two different target dynamics models are considered for the elemental Kalman filters: a linear, Gauss-Markov acceleration model, and a nonlinear, constant turn-rate model.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1994 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Technical Reports Awareness Circular TRAC written by and published by . This book was released on 1988-05 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Vs MAP Multiple Model Adaptive Estimation for Field of View Expansion in Tracking Airborne Targets written by P. A. Loving and published by . This book was released on 1985 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Previous efforts have led to the development of a multiple model adaptive filter (MMAF) tracking algorithm which demonstrates significant improvements in performance against close-range, highly dynamic, airborne targets, over a direct correlation method currently in use. The basic elemental filter in the MMAF bank combines an enhanced correlator and a linear Kalman filter. Digital signal processing techniques are used to derive a target shape function from the forward looking infrared sensor data. This shape function is used as a template in the correlation algorithm which generates offset pseudo-measurements for the update portion of a linear Kalman filter. The multiple models are created by tuning the basic model for best performance against differing target maneuvering behavior and with physically different fields of view. The outputs of three independent elemental filters, each receiving data from a shared sensor are used to generate a single adaptive estimate of the state via a probabilistic weighted average (Bayesian form) or by selection of the one elemental filter associated with the highest probability (MAP form). The adaptive state estimate can produce target position predictions to be used in generating feedback control for maintaining the target in the center of the field of view. There are two main results from this effort. The addition of a third elemental filter to the baseline MMAF improves tracking performance over the two-element MMAF. Specifically, the peak error following a maneuver is significantly reduced. However, the MAP estimation approach does not differ significantly from the Bayesian approach.

Download or read book Proceedings of the 31st IEEE Conference on Decision and Control written by IEEE Control Systems Society and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1992 with total page 954 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiple Target Tracking in the Adaptive Cruise Control Environment Using Multiple Models and Probabilistic Data Association written by Derek Stanley Caveney and published by . This book was released on 2001 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhanced Tracking of Airborne Targets Using Forward Looking Infrared and Laser Return Measurements written by Patrick J. Grondin and published by . This book was released on 1993 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Air Force Institute of Technology has been involved in developing Kalman filter based trackers of ballistic missiles for 15 years. The goal of this thesis is to develop a Multiple Model Adaptive Estimator (MMAE) that tracks the missile plume (using a forward looking infrared sensor) and the missile hardbody center-of-mass (additionally using low energy laser returns) for the purpose of directing a high power laser to incapacitate the missile. The missile plume 'pogos' about an offset equilibrium point (relative to the hardbody center-of-mass) with an amplitude and frequency of oscillation that are not precisely known a priori. The MMAE algorithm estimates these parameters to improve performance in tracking the hardbody center-of-mass. To accomplish this MMAE structure, single Kalman filters were developed and tested at the different parameter values. A Kalman filter residual analysis was used on these working single filters to define the MMAE structure that provided the most effective adaptation and most accurate target tracking. A three-filter MMAE structure gave the lowest hardbody center-of-mass tracking errors. The two-dimensional parameter space, pogo amplitude and frequency, was successfully partitioned according to the frequency of oscillation. When the plume pogo amplitude is large, the MMAE structure substantially reduces the tracking errors of the hardbody center-of-mass, compared to a tracker without adaptive pogo estimation. Kalman filter, Tracking, Infrared, Doppler, Laser.