A formulation of multitarget tracking as an incomplete data problem

Gauvrit, H.; Cadre, J.-P. Le; Jauffret, Claude

doi:10.1109/7.625121

Cited by 116 publications

(49 citation statements)

References 17 publications

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“…Recently, EM has also been proposed in the target-tracking literature to perform smoothing of tracks, leading to the Probabilistic Multi-Hypothesis Tracker (PMHT) (Avitzour, 1992;Streit & Luginbuhl, 1994;Gauvrit, Le Cadre, & Jauffret, 1997). In the PMHT, the same conditional independence assumptions are made as in this paper, and identical expressions are obtained for the virtual measurements in the M-step.…”

Section: Related Workmentioning

confidence: 73%

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et al. 2003

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Abstract. Learning spatial models from sensor data raises the challenging data association problem of relating model parameters to individual measurements. This paper proposes an EM-based algorithm, which solves the model learning and the data association problem in parallel. The algorithm is developed in the context of the the structure from motion problem, which is the problem of estimating a 3D scene model from a collection of image data. To accommodate the spatial constraints in this domain, we compute virtual measurements as sufficient statistics to be used in the M-step. We develop an efficient Markov chain Monte Carlo sampling method called chain flipping, to calculate these statistics in the E-step. Experimental results show that we can solve hard data association problems when learning models of 3D scenes, and that we can do so efficiently. We conjecture that this approach can be applied to a broad range of model learning problems from sensor data, such as the robot mapping problem.

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Section: Related Workmentioning

confidence: 73%

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et al. 2003

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“…In fact, this is due to the combinatorial nature of the data association problem in the multiple source case. To overcome this problem, various approaches have been investigated, either based on mixture modeling and identification [30,31] or, gating and pruning [32]. But, the combinatorial problem is always subjacent.…”

Section: B Multiple Source Casementioning

confidence: 99%

On the convergence of iterative methods for bearings-only tracking

Cadre

Jaetffret²

1999

IEEE Trans. Aerosp. Electron. Syst.

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“…It was implemented using the auction algorithm. Any of the more advanced data association techniques may also be used and these include multiple hypothesis tracking [31], joint probabilistic data association [30] and probabilistic multiple hypothesis tracking [32].…”

Section: B Observation Modelmentioning

confidence: 99%

Joint inference of dominant scatterer locations and motion parameters of an extended target in high range‐resolution radar

Freitas

Villiers

Nel

2015

IET Radar, Sonar & Navigation

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A target of interest measured by a high range resolution radar may be modelled by multiple dominant points of reflections referred to as dominant scatterers. In this paper a non-linear state space setting is used to model the states and measurements of a target moving in the down-and cross-range dimensions. A resample-move particle filter with simulated annealing is successfully used to jointly infer the locations of the dominant scatterers and the motion parameters of the target. A novel technique for the initialization of the particle filter for the given application is presented. The location estimates of scatterers using the particle filter method are compared to those obtained using standard range-Doppler inverse synthetic aperture radar (ISAR) imaging when using the same radar returns for both cases. The particle filter infers the location of scatterers more accurately than range-Doppler ISAR processing, and the processing can be performed online as opposed to ISAR processing, which requires batching. It is relatively straightforward to extend the method to perform localisation and tracking of scatterers in three dimensions, whereas such an extension is challenging in range-Doppler ISAR processing. However, several challenges need be addressed to make this algorithm suitable for practical implementation and these challenges are discussed. This method may be used to obtain very accurate estimates of target state, which may in turn be used for accurate ISAR motion compensation. Given enough computing resources this algorithm may in future become the basis of a new radar target imaging scheme.

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A formulation of multitarget tracking as an incomplete data problem

Cited by 116 publications

References 17 publications

Untitled

Untitled

On the convergence of iterative methods for bearings-only tracking

Joint inference of dominant scatterer locations and motion parameters of an extended target in high range‐resolution radar

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