Observability in passive target motion analysis

Jauffret, Claude; Pillon, Denis

doi:10.1109/7.543850

Cited by 136 publications

(75 citation statements)

References 12 publications

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“…In addition, for the sensor networks, the resolve ability of multiple closely spaced targets with a given sensor measurement model is a basic concept about the sensor systems and an extremely important aspect of their over-all performance [19,20]. Some sensor measurement models have been introduced in [21][22][23]. The information resolution based on statistical manifold is introduced in [24,25] which cannot give an geodesic explicitly expressed in general.…”

Section: Introductionmentioning

confidence: 99%

“…The information resolution based on statistical manifold is introduced in [24,25] which cannot give an geodesic explicitly expressed in general. Meanwhile, as a very important issue for sensor networks, target tracking has also been investigated [22,23,26]. In this paper, the above two aspects are considered by the information submanifold for sensor networks.…”

Section: Introductionmentioning

confidence: 99%

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Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks

Sun

Win

2017

Entropy

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Abstract:In this paper, firstly, manifold PD(n) consisting of all n × n symmetric positive-definite matrices is introduced based on matrix information geometry; Secondly, the geometrical structures of information submanifold of PD(n) are presented including metric, geodesic and geodesic distance; Thirdly, the information resolution with sensor networks is presented by three classical measurement models based on information submanifold; Finally, the bearing-only tracking by single sensor is introduced by the Fisher information matrix. The preliminary analysis results introduced in this paper indicate that information submanifold is able to offer consistent and more comprehensive means to understand and solve sensor network problems for targets resolution and tracking, which are not easily handled by some conventional analysis methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks

Sun

Win

2017

Entropy

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“…The conditions are that the emitted frequency must be constant during observation time and the target is not moving radially. In such situations, the observer can be stationary [15], which is very useful in real applications.…”

Section: Introductionmentioning

confidence: 99%

Maneuvering Target Doppler-Bearing Tracking With Signal Time Delay Using Interacting Multiple Model Algorithms

Bi¹,

Ren²

2008

PIER

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Abstract-For maneuvering target Doppler-bearing tracking with signal time delay, a novel approach called ISE-IMM is proposed in this paper. The iterative state estimation (ISE) method is designed to eliminate the negative influence of time delay effect and an interacting multiple model (IMM) filter is embedded to estimate the state according to the measurements of the delayed signal. The nonlinear filter preferred in this paper is a particle filter (PF) with an improved resampling procedure. Performance of our proposed method is evaluated in Monte Carlo simulations. Results show the effectiveness and stability of ISE-IMM-PF in combating the negative effect of signal time delay.

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“…the platform may still take a trajectory wherefrom the target is unobservable). This analysis was rigorously extended, in the form of a necessary and sufficient condition, in [26], [12], [4], [18]; a comprehensive analysis of observability related to practical scenarios was also conducted in [18]. These results were also demonstrated in discretetime in [14] via linear algebra; observability insights in different scenarios were presented, and also a stochastic observability (and estimability) analysis was performed.…”

Section: B Related Workmentioning

confidence: 99%

Tracking the Tracker from its Passive Sonar ML-PDA Estimates

Ciuonzo

Willett

Bar‐Shalom

2014

IEEE Trans. Aerosp. Electron. Syst.

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Target motion analysis with wideband passive sonar has received much attention. Maximumlikelihood probabilistic data-association (ML-PDA) represents an asymptotically efficient estimator for deterministic target motion, and is especially well-suited for low-observable targets; the results presented here apply to situations with higher signal to noise ratio as well, including of course the situation of a deterministic target observed via "clean" measurements without false alarms or missed detections. Here we study the inverse problem, namely, how to identify the observing platform (following a "two-leg" motion model) from the results of the target estimation process, i.e. the estimated target state and the Fisher information matrix, quantities we assume an eavesdropper might intercept. We tackle the problem and we present observability properties, with supporting simulation results. Index TermsEavesdropper, Fisher information matrix, ML-PDA, nonlinear identification, platform localization, stealthy platform, wideband passive sonar. P. K.

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Observability in passive target motion analysis

Cited by 136 publications

References 12 publications

Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks

Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks

Maneuvering Target Doppler-Bearing Tracking With Signal Time Delay Using Interacting Multiple Model Algorithms

Tracking the Tracker from its Passive Sonar ML-PDA Estimates

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