Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Virtual Measurement Model

Hoher, Patrick; Wirtensohn, Stefan; Baur, Tim; Reuter, Johannes; Govaers, Felix; Koch, Wolfgang

doi:10.1109/tsp.2021.3138006

Cited by 12 publications

(16 citation statements)

References 24 publications

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“…If n θ = n z = ∞, (7) gives an exact representation of any continuous function on the outer surface of a finite cylinder. However, because of computational reasons, we restrict the sums in (7) to be finite.…”

Section: Coordinatesmentioning

confidence: 99%

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Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Baur

Reuter

Zea

et al. 2022

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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With the high resolution of modern sensors such as multilayer LiDARs, estimating the 3D shape in an extended object tracking procedure is possible. In recent years, 3D shapes have been estimated in spherical coordinates using Gaussian processes, spherical double Fourier series or spherical harmonics. However, observations have shown that in many scenarios only a few measurements are obtained from top or bottom surfaces, leading to error-prone estimates in spherical coordinates. Therefore, in this paper we propose to estimate the shape in cylindrical coordinates instead, applying harmonic functions. Specifically, we derive an expansion for 3D shapes in cylindrical coordinates by solving a boundary value problem for the Laplace equation. This shape representation is then integrated in a plain greedy association model and compared to shape estimation procedures in spherical coordinates. Since the shape representation is only integrated in a basic estimator, the results are preliminary and a detailed discussion for future work is presented at the end of the paper.

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Section: Coordinatesmentioning

confidence: 99%

“…Explicit shapes can be used if prior knowledge is available or computation time is to be kept low. Elliptical shapes [3], [4], [5], [6], [7] can be applied in various applications for different sensors such as LiDAR or RADAR. An overview of elliptic EOT can be found in [8].…”

Section: Introductionmentioning

confidence: 99%

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Baur

Reuter

Zea

et al. 2022

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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“…)) is a zero-mean white Gaussian noise of radius function with the following variance Then, substitute the above equations into (18), the target-originated measurement in polar coordinate can be rewritten as…”

Section: Dynamic and Measurement Modelsmentioning

confidence: 99%

“…Many ETT methods have been proposed in the last decades, such as Sequential Monte Carlo (SMC) [12,13], Random Matrix (RM) [14][15][16][17][18], Random Hypersurface Models (RHM) [19][20][21], Gaussian Processes based ETT (GP-ETT) [6,22,23], and so on. Among these works, the GP has the ability to model and learn an unknown radius function of an irregular-shape target analytically and can provide benefits toward higher-precision contour estimation [24].…”

mentioning

confidence: 99%

Gaussian processes based extended target tracking in polar coordinates with input uncertainty

Guo

Yang

Liu

et al. 2022

EURASIP J. Adv. Signal Process.

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Gaussian processes (GP) based extended target tracking (ETT) technique has attracted the attention of scientists since it can accurately estimate the kinematic states as well as the contour states of irregular-shape targets. Most traditional GP methods consider the ETT problem with a linear measurement model in Cartesian coordinates and ignore the input uncertainty of GP for simplicity. In many applications, however, measurements are generated with high-resolution sensors in polar coordinates. More importantly, the ignorance of input uncertainty in GP will exacerbate the tracking performance in these cases. In order to track an irregular-shape extended target in polar coordinates with input uncertainty, an improved GP-based probabilistic data association (IGP-PDA) algorithm is developed that includes the following enhancements: Firstly, a nonlinear measurement model is used and the unbiased converted measurement technique is invoked for the ETT problem. Secondly, the analytical form of statistical properties of the input uncertainty due to measurements noise and predicted error is derived. Thirdly, an IGP-PDA taking into account measurement origin uncertainty as well as input uncertainty is proposed, and three sub-optimal implementations are provided. Last, the posterior Cramer-Rao lower bound of ETT with input uncertainty is derived. Simulation results verify the effectiveness of the proposed method.

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“…However, if multiple resolution cells of the sensor are occupied by a target, for example, in vehicle tracking using automotive radar, the target is regarded as an extended target [9]. In such a case, each target can give rise to multiple measurements [10]. Only point targets will be discussed below.…”

Section: Introductionmentioning

confidence: 99%

A New Coarse Gating Strategy Driven Multidimensional Assignment for Two-Stage MHT of Bearings-Only Multisensor-Multitarget Tracking

Wei

Duan

Han

et al. 2022

Sensors

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The problem of two-dimensional bearings-only multisensor-multitarget tracking is addressed in this work. For this type of target tracking problem, the multidimensional assignment (MDA) is crucial for identifying measurements originating from the same targets. However, the computation of the assignment cost of all possible associations is extremely high. To reduce the computational complexity of MDA, a new coarse gating strategy is proposed. This is realized by comparing the Mahalanobis distance between the current estimate and initial estimate in an iterative process for the maximum likelihood estimation of the target position with a certain threshold to eliminate potential infeasible associations. When the Mahalanobis distance is less than the threshold, the iteration will exit in advance so as to avoid the expensive computational costs caused by invalid iteration. Furthermore, the proposed strategy is combined with the two-stage multiple hypothesis tracking framework for bearings-only multisensor-multitarget tracking. Numerical experimental results verify its effectiveness.

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Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Virtual Measurement Model

Cited by 12 publications

References 24 publications

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Gaussian processes based extended target tracking in polar coordinates with input uncertainty

A New Coarse Gating Strategy Driven Multidimensional Assignment for Two-Stage MHT of Bearings-Only Multisensor-Multitarget Tracking

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