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Adaptive sensor management in target tracking

Adaptive sensor management in target tracking

引用

14th conference on signal and data processing of small targets

作者： Sworder, DD Boyd, JE Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)0819444782

Model-based. path estimation algorithms are commonly derived from a linear kinematic equation and an expansive observation model. the premise that the measurement region is all-inclusive simplifies the performance analysis, but it does not describe the relevant characteristics of some sensors. Most sensors have an active region. If the region contains, the target. a noisy location measurement is made. Alternatively, no location measurement is returned. there is a clear tradeoff between measurement acuity and broad coverage. A sensor that adapts its active region to the most likely target location should achieve higher quality tracking and identification. However. effective utilization of this flexibility requires an accurate determination of the conditional distribution of the target-state. In this paper, the Gaussian Wavelet Estimator is used in an adaptive algorithm for sensor management. It is shown that the adaptive window provides performance that is superior to that achieved using a fixed window of comparable cover probability.

关键词： nonlinear filters target tracking data fusion

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On track and tracklet fusion filtering

On track and tracklet fusion filtering

引用

14th conference on signal and data processing of small targets

作者： Drummond, OE CyberRnD Inc Culvar City CA 90230 USA

ISBN: (纸本)0819444782

Track and tracklet fusion filtering is complicated because the estimation errors of tracks from two sources for the same target may be cross-correlated. this cross-correlation of these errors should be taken into account when designing the filter used to combine the track data. this paper addresses the various track and tracklet fusion methods and their impact on communications load and tracking characteristics. In track and tracklet fusion a sequence of measurements is processed at the sensor or platform level to form tracks;then sensor level track data (in the form of tracks or tracklets) for a target is distributed and fused with each other or with a global track. Track Fusion and Tracklet Fusion are also sometimes called Hierarchical Fusion, Federated Fusion, or Distributed Fusion. Track data can include features or other information useful for target classification. One characteristic of track and tracklet fusion that distinguishes one method from another is whether the local track data is combined or if global tracks are maintained and updated using the sensor track data. Another important issue is whether there is filter process noise to accommodate target maneuvers. Some filtering methods are designed for maneuvering targets and others are not. this paper enumerates the various track and tracklet fusion methods for processing data from distributed sensors and their impact on filter performance and communications load.

关键词： target tracking multiple sensor tracking track fusion multiple target tracking sensor data fusion Bayesian methods tracklet distributed tracking estimation and filtering

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An MDL approach for multiple low observable track initiation

An MDL approach for multiple low observable track initiation

引用

14th conference on signal and data processing of small targets

作者： Chen, H Kirubarajan, T Bar-Shalom, Y Pattipati, KR Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)0819444782

In this paper the track initiation problem is formulated as multiple composite hypothesis testing using maximum likelihood estimation with probabilistic data association (ML-PDA), an algorithm known to work under very low SNR conditions. this algorithm does not have to make a decision as to which measurement is target originated. the hypothesis testing is based on the minimum description length (MDL) criterion. We first review some well-known approaches for statistical model selection and the advantage of the MDL criterion. then we present an approximate penalty in accounting for the model complexity to simplify the calculation of MDL. Finally, we apply the. MDL approach for the detection and initiation of tracks of incoming tactical ballistic missiles in the exo-atmospheric phase using a surface based electronically scanned array (ESA) radar. the targets are characterized by low SNR, which leads to low detection probability and high false alarm rate. the target acquisition problem is formulated using a batch of radar scans to detect the presence of up to two targets. the ML-PDA estimator is used to initiate the tracks assuming the target trajectories follow a deterministic state propagation. the approximate MDL criterion is used to determine the number of valid tracks in a surveillance region. the detector and estimator are shown to be effective even at 4.4 dB average SNR in a resolution cell (at the end of the signal processing chain).

关键词： track initiation minimum description length maximum likelihood estimator probabilistic data association model selection

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On expectation maximization applied to GMTI convoy tracking

On expectation maximization applied to GMTI convoy tracking

引用

14th conference on signal and data processing of small targets

作者： Koch, W FGAN FKIE D 53343 Wachtberg Neuenahrer Strasse 20 Germany

ISBN: (纸本)0819444782

Collectively moving ground targets are typical of a military ground situation and have to be treated as separate aggregated entities. For a long-range ground surveillance application with airborne GMTI radar we in particular address the task of track maintenance for ground moving convoys consisting of a small number of individual vehicles. In the proposed approach the identity of the individual vehicles within the convoy is no longer stressed. their kinematical state vectors are rather treated as internal degrees of freedom characterizing the convoy. which is considered as a collective unit. In this context, the Expectation Maximization technique (EM), originally developed for incomplete data problems in statistical inference and first applied to tracking applications by STREIT et al. [1, 2], seems to be a promising approach. We suggest to embed the EM algorithm into a more traditional Bayesian tracking framework for dealing with false or unwanted sensor returns. the proposed distinction between 'external' and 'internal' data association conflicts (i.e. those among the convoy vehicles) should also enable the application of sequential track extraction techniques introduced by VAN KEUK [3] for aircraft formations, providing estimates of the number of the individual convoy vehicles involved. Even with sophisticated signal processing methods (STAP: Space-Time Adaptive processing). ground moving vehicles can well be masked by the sensor specific clutter notch (Doppler blinding). this physical phenomenon results in interfering fading effects, which can well last over a longer series of sensor updates and therefore will seriously affect the track quality unless properly handled. Moreover, for ground moving convoys the phenomenon of Doppler blindness often superposes the effects induced by the finite resolution capability of the sensor. In many practical cases a separate modeling of resolution phenomena for convoy targets can therefore be omitted, provided the GMTI detectio

关键词： Ground Moving targets (GMT) Expectation Maximization (EM) Bayesian/Probabilistic Multiple Hypothesis Tracking (PMHT, MHT, PDA) Minimum Detectable Velocity (MDV) Doppler blinding sensor resolution phenomena

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Adaptive mean and variance filter for detection of dim point-like targets

Adaptive mean and variance filter for detection of dim point...

引用

14th conference on signal and data processing of small targets

作者： Lim, ET Shue, L Venkarteswarlu, R Nanyang Technol Univ Ctr Signal Proc Singapore 639798 Singapore

ISBN: (纸本)0819444782

the problem of detecting small target in IR imagery has attracted much research effort over the past few decades. As opposed to early detection algorithms which detect targets spatially in each image and then apply tracking algorithm, more recent approaches have used multiple frames to incorporate temporal as well as spatial information. they often referred to as "track before detect" algorithms. this approach has shown promising results particularly for detection of dim point-like targets. However, the computationally complexity has prohibited practical usage for such algorithms. this paper presents an adaptive, recursive and computation efficient detection method. this detection algorithm updates parameters and detects occurrence of targets as new frame arrived without storing previous frames, thus achieved recursiveness. Besides, the target temporal intensity change is modeled by two Gaussian distribution with different mean and variance. the derivation of this generalized model has taken account of the wide variation of target speed, therefore detects wider range of targets.

关键词： small target temporal filter triple temporal filter continuous wavelet transform

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Track-to-track association and bias removal

Track-to-track association and bias removal

引用

14th conference on signal and data processing of small targets

作者： Stone, LD Williams, ML Tran, TM Metron Inc Reston VA 20190 USA

ISBN: (纸本)0819444782

this paper develops methods for associating two sets of sensor tracks in the presence of missing tracks and translation bias. Key results include (1) Extension of the Maximum A Posteriori Probability method of matching tracks to use feature information as well as kinematic information;(2) translation bias removal techniques that are computationally tractable for large numbers of tracks, and effective in the presence of missing tracks. these methods were evaluated by Monte Carlo simulation. the experimental results indicate that the Maximum A Posteriori Probability method with its adaptive threshold achieves close to its best performance for matching tracks without an additional threshold adjustment.

关键词： Sensors Target detection Monte Carlo methods Computer programming Fourier transforms Computer simulations Detection and tracking algorithms signal to noise ratio Kinematics Copper

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Passive relative ranging applied to sensor-to-sensor data association

Passive relative ranging applied to sensor-to-sensor data as...

引用

14th conference on signal and data processing of small targets

作者： Grantham, JL Brahm, SJ Zounes, RS Whitt, E Comp Sci Corp Huntsville AL 35802 USA

ISBN: (纸本)0819444782

Ballistic Missile Defense (BMD) effectiveness depends on a system's capability to acquire, track, identify, and engage threat missiles. the probability of a successful engagement can be improved by performing multiple-sensor data fusion, especially if the participating sensor systems are based on both radar frequency (RF) and infrared (IR) phenomenology. In this paper, we apply this observation to the "Target Object Map (TOM) correlation problem" for the standard configuration of a kill vehicle (with a single or multicolor IR seeker) receiving uplinks from a ground based radar. Specifically, we examine the application of a relative ranging technique that augments the angles-only track information of a passive IR sensor with non-parametric range-ranking of the threat complex. Since data association performance is significantly better for three-dimensional (3-D) matching than for two-dimensional (2-D) matching, the idea is to take advantage of relative range-ranking information of the threat complex to potentially improve performance. Numerous techniques that attempt to extract absolute range estimates from a passive IR sensor have been investigated by researchers in the BMD community and it is understood that range information allows for improved threat tracking, radiant intensity estimates, and data association performance. However, extracting absolute target range estimates from irrdiance measurements is extremely difficult because of the presence of data uncertainties / ambiguities, environment and sensor noises, and small angular rates of tracked objects. Passive Relative Ranging (PRR) is distinct in that it focuses on the "relative" range-ranking of objects;knowledge that one object is closer than a second object, while not relevant for improving track or intensity estimation performance, can possibly improve the performance of sensor-to-sensor object assignment. the proposed PRR technique is based on the physical range-squared relationship between intensity and

关键词： passive relative ranging data association passive ranging target object map Cramer-Rao bound

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Efficient multi-sensor resource management using Cramer-Rao lower bounds

Efficient multi-sensor resource management using Cramer-Rao ...

引用

14th conference on signal and data processing of small targets

作者： Hernandez, ML Kirubarajan, T Bar-Shalom, Y QinetiQ Ltd Malvern Technol Ctr Malvern WR14 3PS Worcs England

ISBN: (纸本)0819444782

this paper describes the development of a general framework for the efficient management of multiple sensors in target tracking. the basis of the technique is to quantify, and subsequently control, the accuracy of target state estimation. the Posterior Cramer-Rao lower bound provides the means of achieving this aim by enabling us to determine a bound on the performance of all unbiased estimators of the unknown target state. the general approach is then to use optimization techniques to control the measurement process in order to achieve accurate target state estimation. We are concerned primarily with the deployment and utilization of a limited sensor resource. We also allow for measurement origin uncertainty, with sensor measurements either target generated or false alarms. We exploit previous work to determine a general expression for the Fisher Information Matrix in this case. We show that by making certain assumptions we can express the measurement uncertainty as a constant information reduction factor. this enables the Fisher Information Matrix to be calculated quickly, allowing Cramer-Rao bounds to be utilized for real-time, online sensor management. An example is presented in which the aim is to track a submarine by deploying a series of passive sonobuoys. the target moves according to a constant velocity model, and each sonobuoy provides bearings-only measurements. We show that the sensor management framework determines quick deployment strategies. this enables the target to be accurately localized, and at the same time makes efficient use of the limited sensor resource.

关键词： sensor management data fusion Posterior Cramer-Rao lower bound Fisher Information Matrix target state estimation

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Tracking with asynchronous multiple sensors

Tracking with asynchronous multiple sensors

引用

13th conference on signal and data processing of small targets

作者： Gray, JE McCabe, DH USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819441872

Sensor data fusion has long been recognized as a means to improve target tracking. Common practice assumes that the sensors used are synchronous (i.e., perform the, same operation at the identical time), take measurements at the same time and have no communication delays between sensor platforms and the central processing center. Such assumptions are not valid in practice. this paper removes these assumptions when dealing with multisensor target tracking. In particular, it assumes that the sensors used can have different data rates and communication delays between local and central platforms. A new tracking algorithm using asynchronous sensors is proposed and derived in this paper.

关键词： Filtering (signal processing) Lithium Sensors Silicon Zinc Electronic filtering Lutetium data communications data processing signal processing

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Tracking airborne targets occasionally hidden in the blind Doppler

Tracking airborne targets occasionally hidden in the blind D...

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13th conference on signal and data processing of small targets

作者： Gordon, NJ Ristic, BO QinetiQ Ltd Malvern WR14 3PS Worcs England

ISBN: (纸本)0819441872

this paper describes an application of sequential Monte Carlo estimation (particle filtering) to the problem of tracking targets occasionally hidden in the blind Doppler zones of a radar. A particle filter which incorporates the prior knowledge of the blind Doppler zone limits has been designed. the simulation results suggest significant improvement in track continuity over the standard Extended Kalman filter. As an operationally viable solution a hybrid tracker is envisaged which can switch between the EKF (with possibly built-in data association logic) and the particle filter, depending on the tracking conditions.

关键词： target tracking blind Doppler Bayesian methods bootstrap filter particle filter

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