Observability in passive target motion analysis
01 Oct 1996-IEEE Transactions on Aerospace and Electronic Systems (IEEE)-Vol. 32, Iss: 4, pp 1290-1300
TL;DR: In this paper, the nature of observability of nonlinear systems encountered in passive target motion analysis (TMA) is examined and the approach proposed is based upon a well-chosen criterion which allows us to answer the major observability questions.
Abstract: The nature of observability of nonlinear systems encountered in passive target motion analysis (TMA) is carefully examined. The approach proposed here is based upon a well-chosen criterion which allows us to answer the major observability questions.
Citations
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TL;DR: The aim of this work is to identify those relative sensor-target geometries which result in a measure of the uncertainty ellipse being minimized, and to show that an optimal sensor- target configuration is not, in general, unique.
393 citations
TL;DR: Three tracking algorithms are proposed and compared to the theoretical bound of the performance error, and the interactive multiple model (IMM) algorithm with extended Kalman filters and the multi-mode particle filter are proposed.
165 citations
07 Jun 2004
TL;DR: It is shown that all but a small class of trajectories can be estimated and explicitly characterize those trajectories that can be asymptotically estimated.
Abstract: Navigation technology is considered that enables an underwater vehicle to compute its trajectory in real-time by utilizing range measurements from a single known location. This concept is especially attractive for small underwater vehicles where more traditional navigation technology is prohibitive due to volume constraints. By assessing local observability of the underwater vehicle and available measurements about potential vehicle trajectories, we explicitly characterize those trajectories that can be asymptotically estimated. It is shown that all but a small class of trajectories can be estimated.
109 citations
TL;DR: In this article, a batch-recursive estimator for tracking maneuvering targets from bearings-only measurements in clutter is presented, which combines the batch maximum likelihood-probabilistic data association (ML-PDA) estimator with the recursive interacting multiple model (IMM) with probabilistic Data Association (PDA).
Abstract: We present a new batch-recursive estimator for tracking maneuvering targets from bearings-only measurements in clutter (i.e., for low signal-to-noise ratio (SNR) targets), Standard recursive estimators like the extended Kalman Iter (EKF) suffer from poor convergence and erratic behavior due to the lack of initial target range information, On the other hand, batch estimators cannot handle target maneuvers. In order to rectify these shortcomings, we combine the batch maximum likelihood-probabilistic data association (ML-PDA) estimator with the recursive interacting multiple model (IMM) estimator with probabilistic data association (PDA) to result in better track initialization as well as track maintenance results in the presence of clutter. It is also demonstrated how the batch-recursive estimator can be used for adaptive decisions for ownship maneuvers based on the target state estimation to enhance the target observability. The tracking algorithm is shown to be effective for targets with 8 dB SNR.
83 citations
Cites background from "Observability in passive target mot..."
...The problem of observability in bearings-only tracking is discussed further in [ 10 , 16, 18, 20]....
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...The problem of observability in bearings-only tracking is discussed further in [10, 16, 18, 20 ]....
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TL;DR: This work shows that optimal disambiguation can be pursued by deriving the full Bayesian posterior distribution of the target state by means of particle filtering techniques, and corroborated by simulations that show the effectiveness of the particle-filtering tracking.
Abstract: Port-starboard ambiguity is an important issue in underwater tracking systems with anti-submarine warfare applications, especially for wireless sensor networks based upon autonomous underwater vehicles. In monostatic systems this ambiguity leads to a ghost track of the target symmetrically displaced with respect to the sensor. Removal of such artifacts is usually made by rough and heuristic approaches. In the context of Bayesian filtering approximated by means of particle filtering techniques, we show that optimal disambiguation can be pursued by deriving the full Bayesian posterior distribution of the target state. The analysis is corroborated by simulations that show the effectiveness of the particle-filtering tracking. A full validation of the approach relies upon real-world experiments conducted by the NATO Science and Technology Organization - Centre for Maritime Research and Experimentation during the sea trials Generic Littoral Interoperable Network Technology 2011 and Exercise Proud Manta 2012, results which are also reported.
78 citations
References
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TL;DR: The properties of controllability, observability, and the theory of minimal realization for linear systems are well-understood and have been very useful in analyzing such systems as discussed by the authors.
Abstract: The properties of controllability, observability, and the theory of minimal realization for linear systems are well-understood and have been very useful in analyzing such systems. This paper deals with analogous questions for nonlinear systems.
2,306 citations
TL;DR: In this paper, the problem of estimating the position and velocity of an object from noise corrupted bearing measurements obtained by a single moving observation platform is considered and a maximum likelihood estimate (MLE) of the target motion analysis solution is developed and its performance analyzed.
Abstract: This paper considers the problem of estimating the position and velocity of an object from noise corrupted bearing measurements obtained by a single moving observation platform. The process is inherently nonlinear and exhibits unusual observability properties that are geometry-dependent. A maximum likelihood estimate (MLE) of the target motion analysis solution is developed and its performance analyzed. A comparison is drawn between the MLE and two previously reported methods, a nonlinear modified-instrumental variable estimate (MIV) and the pseudo-linear estimate (PLE). Both the MIV and PLE are shown to derive from approximations to the nonlinear measurement equation and therefore share some common properties with the MLE. The limits on performance that can be expected from processing bearing data are detailed. Specifically, for long range-to-baseline geometries, approximate expressions for the Cramer-Rao bound are derived. Extension of the results to the practical filters approximately predicts numerically observed behavior. For less restrictive geometries, bounds are presented. Incorporation of a target speed constraint on the MLE results in a transition to a lower dimensional problem as noise level and range increases. Monte Carlo experimental results are presented and the improvements realized by the MLE techniques are evident.
495 citations
TL;DR: In this paper, the observability requirements for bearings-only target motion analysis (TMA) were rigorously established by solving a third-order nonlinear differential equation, and closed form expressions were developed and subsequently used to specify necessary and sufficient conditions on own-ship motion that insure a uniquetracking solution.
Abstract: The observability requirements for bearings-only target motion analysis (TMA) are rigorously established by solving a third-order nonlinear differential equation. Closed form expressions are developed and subsequently used to specify necessary and sufficient conditions on own-ship motion that insure a uniquetracking solution. It is shown that for certain types of maneuvers the estimation process remains unobservable, even when the associated bearing rate is nonzero. Such maneuvers are frequently overlooked in heuristic discussions of TMA observability, which may account for some common misconceptions regarding the characteristics of acceptable own-ship motion.
377 citations
TL;DR: Target motion analysis from a narrowband passive sonar that yields bearing and frequency measurements in the presence of false detections (clutter) in a low-SNR (low signal-to-noise ratio) environment is discussed.
Abstract: Target motion analysis from a narrowband passive sonar that yields bearing and frequency measurements in the presence of false detections (clutter) in a low-SNR (low signal-to-noise ratio) environment is discussed. The likelihood function used to compute the maximum likelihood estimation of the track parameters (localization and frequency) incorporates the false alarms via the probabilistic data association technique. The Cramer-Rao lower bound is calculated and results obtained from simulations are shown to be compatible with it. A test of track acceptance is also presented. >
170 citations
TL;DR: In this paper, necessary and sufficient conditions for the observability of the target's Nth-order dynamics, given direction measurements, were presented, and the derivations are extremely simple and do not require the examination of an observability matrix or nonlinear differential equations.
Abstract: Necessary and sufficient conditions are presented for the observability of the target's Nth-order dynamics, given direction measurements. The derivations are extremely simple and do not require the examination of an observability matrix or nonlinear differential equations. Previously published observability requirements for the first-order dynamics are shown to be necessary but not sufficient. >
162 citations