Adaptive tracking of maneuvering targets

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Naval Postgraduate School , Monterey, California
Tracking radar, Radar in navig
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The requirements of a track-while-scan radar data processing scheme are stated from the point of view of the evader in a pursuit-evasion game. The rules of the game, determined in part by the nature of the pursuer"s weapons, are such that the evader must be able to discriminate reliably between straight-line and maneuvering pursuer motion. A suggested method for such discrimination is tested by simulation. The method employs bias-sensitive maneuver detection and gain-adaptive discrete Kalman filtering. Also tested is a smoothing scheme for establishing long-term trends in a pursuer"s maneuvering track. The outcome of both tests indicate that the suggested processing methods may be useful in the formulation of fire control policies for destruction of maneuvering targets. (Author)

Statementby James S. Demetry and Harold A. Titus
ContributionsTitus, Harold A., Naval Postgraduate School (U.S.)
The Physical Object
Pagination34 p. :
ID Numbers
Open LibraryOL25513096M
OCLC/WorldCa435549135

The purpose of this chapter is to Adaptive tracking of maneuvering targets book state estimation techniques than can “adapt” themselves to certain types of uncertainties beyond those treated in earlier chapters—adaptive estimation algorithms.

One type of uncertainty to be considered is the case of unknown inputs into the system, which typifies maneuvering targets. Maneuvering target tracking methods mainly include maneuver detection algorithm and adaptive tracking algorithm.

Maneuver detection and adaptive tracking algorithm has its own advantages and disadvantages. The standard multi-model adaptive Kalman filter exits divergence and poor maneuver adaptation. For the above shortcoming, a modification to the standard multi-model adaptive Kalman.

Moose R.L. () Adaptive Range Tracking of Underwater Maneuvering Targets Using Passive Measurements. In: Chen C.H. (eds) Issues in Acoustic Signal — Image Processing and Recognition. NATO ASI Series (Series F: Computer and System Sciences), vol by: 5.

A MATLAB computer program, which will simulate the adaptive tracking of maneuvering targets as a benchmark problem, is included on a computer diskette so that other researchers can implement and.

It is also expected that the adaptive tracking filter shows good tracking performances for any kind of maneuver. A PRACTICAL ADAPTIVE TRACKING FILTER FOR MANEUVERING TARGETS Target Dynamics A target model is to be simply modeled for real-time im­plementation while it describes the target motion accu­: T.K.

Sung, J.G. Lee. This paper presents a novel approach to the adaptive tracking of maneuvering targets using Kalman filter.

The adaptation technique is achieved by constructing a pursuing system of two stages. Because the complexity of the objectives of the actual target movement, Issue 1 JIN Xue-bo, et al. / Maneuvering target tracking by adaptive statistics model any a priori model can not have a remarkable effectiveness.

One of the main shortcomings of the Singer model is that the target acceleration has zero mean at any by: Maneuvering Target Tracking Using Current Statistical Model Based Adaptive UKF for Wireless Sensor Adaptive tracking of maneuvering targets book.

Xiaojun Peng 1,2, Kuntao Yang, and Chang Liu2. 1 School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan,China. 2 Wuhan Second Ship Design Research Institute, Wuhan,China.

Email: {kingarthurpeng. Summary. This chapter is devoted to present two adaptive fuzzy filters with online structure and parameter learning ability with an important feature that they can dynamically partition the input and output spaces using a modified FCM (Fuzzy CMeans) clustering algorithm according to Cited by: 1.

In this paper a parameter identification model is presented. This model identifies the target’s trajectory dynamically, adapts to the variation of working cycle, and covers kinds of possible state of the maneuvering target.

An adaptive filtering is then employed to analyze the tracking. We call it as a whole adaptive tracking in this paper. Key Words: Target Tracking, Adaptive Filtering, Maneuver Detection, Survey 1 Introduction This is the fourth part of a series of papers that provide a comprehensive survey of the techniques for tracking maneuvering targets without addressing the so-called measurement-originuncertainty.

Part I [1] and Part II [2] deal with general target mo. The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure.

In this paper, an adaptive algorithm for tracking maneuvering targets based on neural networks is proposed. This algorithm is implemented with two filters based on the current statistical model and a multilayer feedforward neural network.

T1 - Adaptive disturbance rejection guidance law for visual tracking of a maneuvering target. AU - Stepanyan, Vahram. AU - Hovakimyan, Naira.

PY - Y1 - N2 - This paper presents an adaptive disturbance rejection control architecture for a flying vehicle to track a maneuvering target using a monocular camera as a visual by: 2.

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Shah, H & Morrell, DAn adaptive zoom algorithm for tracking targets using pan-tilt-zoom cameras. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. vol. 2, Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Que, Canada, 5/17/Cited by: Fig.1 The encounter of bearings-only maneuvering target tracking using two sensors The General MM Estimation and Its Limitation The MM approach is widely used in the field of maneuvering target tracking, however, it is noted that some priori information of the target maneuvering feature is required and known before the MM structure is.

This paper puts forward a "current model" concept of maneuvering means that when a target is maneuvering with a certain acceleration at present,the region of acceleration which can be taken in the next instant is limited,and is always around "current" ore,it is unnecessary to take all of the acceleration value of targets into account during the establishing of.

In the existing process of maneuvering target tracking, the target’s actual trajectory can not be foreseen precisely. A commonly attempt is under the assumption that the target’s trajectory is prefixed. The prefixed model is usually not inosculated with the target’s actual trajectory, and the target’s tracking precision can not be by: 3.

Ozkan Target Tracking Novem 4 / 23 Maneuvers Maneuvers are the model mismatch problems in target tracking. Using a high order kinematic model that allows versatile tracking is not a solution in the case where data origin uncertainty is present.

Instead it makes the gates unnecessarily large and makes lter susceptible to Size: 1MB. Distributed state estimation plays a key role in space situation awareness via a sensor network. This paper proposes two adaptive consensus-based unscented information filters for tracking target with maneuver and colored measurement noise.

The proposed filters can fulfill the distributed estimation for non-linear systems with the aid of a consensus strategy, and can reduce the impact of Cited by: 2.

Abstract: The decision-based models for maneuvering target tracking were studied in this paper. Focusing on the problem of dissatisfied with single model tracking and the optimal model-set is difficult to design of the multiple-model (MM) algorithm, we modified the “current ” model, and proposed an adaptive single model (ASM) to track angular motion.

Description Adaptive tracking of maneuvering targets PDF

Lu, G. Zhang, S. Ferrari, M. Anderson, and R. Fierro “A particle-filter information potential method for tracking and monitoring maneuvering targets using a mobile sensor agent,” The Journal of Defense Modeling and Simulation: Applications, Methodologym Technology, June Ricker, G.

and Williams, J. () Adaptive tracking filter for maneuvering targets, IEEE Transactions on Aerospace and Electronic Systems, 14 (1), – Ristic, B. and Morelande, M.

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() Comments on: Cramer–Rao lower bound for tracking multiple targets, in Proceedings of the IET Radar Sonar Navigation, 1 (1), 74–Cited by: We proposed a joint multi-modal sensing mode based on using dynamic agility selection to optimize the tracking performance of multiple maneuvering targets.

The proposed method jointly designs waveforms for radar sensing and resolution switching modes for EO sensing, when both sensor measurements experience high false alarm by: 6.

The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers.

The equivalent-noise approach converts the problem of maneuvering target tracking to that of state Cited by: Suppose instead that we are trying to track a maneuvering target, by which I mean an object with control inputs, such as a car along a road, an aircraft in flight, and so on.

In these situations the filters perform quite poorly. Alternatively, consider a situation such as tracking a sailboat in the ocean.

Aiming at improving the accuracy and quick response of the filter in nonlinear maneuvering target tracking problems, the Interacting Multiple Models Cubature Information Filter (IMMCIF) is proposed.

In IMMCIF, the Cubature Information Filter (CIF) is brought into Interacting Multiple Model (IMM), which can not only improve the accuracy but also enhance the quick response of the by: 4. Bearing only Tracking of Maneuvering Targets using a Single Coordinated Turn Model rishnan Cochin University Kerala, India K.G Balakrishnan Cochin University Kerala, India ABSTRACT The passive tracking of manoeuvring objects using line of sight (LOS) angle measurements only is an important field of research.

tracking performance. Considering that the changing maneuver strategy of target has been neglected in most existing tracking algorithms [2~4] and meanwhile not many of them utilized IF to fuse multi-group measurements provided by observation platform [5~8], a self-adaptive tracking algorithm under Multi-Motion and Multi-maneuver strategies.

targets used for target tracking. Models for all three phases (i.e., boost, coast, and reentry) of motion are covered. Key Words: Target Tracking, Maneuvering Target, Dynamics Model, Ballistic Target, Survey 1 Introduction A survey of dynamics models used in maneuvering target tracking has been reported in [1].

It, however, does not coverFile Size: KB. Survey of Maneuvering Target Tracking. Part I: Dynamic Models X. RONG LI, Senior Member, IEEE VESSELIN P. JILKOV, Member, IEEE University of New Orleans This is the first part of a comprehensive and up-to-date survey of the techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty.

It. An IMM Algorithm for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment and others. Generally, target motion models can be divided into two subcategories: the uniform motion model and the maneuvering model.

A maneuvering target moving .In this paper, a joint adaptive sampling interval and power allocation (JASIPA) scheme based on chance-constraint programming (CCP) is proposed for maneuvering target tracking (MTT) in a multiple opportunistic array radar (OAR) system.

In order to conveniently predict the maneuvering target state of the next sampling instant, the best-fitting Gaussian (BFG) approximation is introduced and used.the target. The tracking of maneuvering targets may be complicated by the fact that acceleration may not be directly observable or measurable.

Additionally, apparent acceleration can be induced by a variety of sources including human input, autonomous guidance, or atmospheric disturbances. Several approaches to File Size: KB.