scholarly journals Tracking Multiple Marine Ships via Multiple Sensors with Unknown Backgrounds

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5025 ◽  
Author(s):  
Cong-Thanh Do ◽  
Tran Thien Dat Nguyen ◽  
Weifeng Liu
Keyword(s):  
State Of The Art ◽  
Numerical Study ◽  
Probability Of Detection ◽  
Multitarget Tracking ◽  
Time Varying ◽  
Multiple Sensors ◽  
Doppler Data ◽  
Online Tracking ◽  
Bernoulli Filter ◽  
Parallel Estimation

In multitarget tracking, knowledge of the backgrounds plays a crucial role in the accuracy of the tracker. Clutter and detection probability are the two essential background parameters which are usually assumed to be known constants although they are, in fact, unknown and time varying. Incorrect values of these parameters lead to a degraded or biased performance of the tracking algorithms. This paper proposes a method for online tracking multiple targets using multiple sensors which jointly adapts to the unknown clutter rate and the probability of detection. An effective filter is developed from parallel estimation of these parameters and then feeding them into the state-of-the-art generalized labeled multi-Bernoulli filter. Provided that the fluctuation of these unknown backgrounds is slowly-varying in comparison to the rate of measurement-update data, the validity of the proposed method is demonstrated via numerical study using multistatic Doppler data.

scholarly journals Tracking Multiple Targets from Multistatic Doppler Radar with Unknown Probability of Detection

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1672 ◽  
Author(s):  
Cong-Thanh Do ◽  
Hoa Nguyen
Keyword(s):  
Detection Probability ◽  
Doppler Radar ◽  
Probability Of Detection ◽  
False Alarms ◽  
Multitarget Tracking ◽  
Time Varying ◽  
Multiple Targets ◽  
Radar Systems ◽  
Unknown Probability ◽  
Multistatic Radar

The measurements from multistatic radar systems are typically subjected to complicated data association, noise corruption, missed detection, and false alarms. Moreover, most of the current multistatic Doppler radar-based approaches in multitarget tracking are based on the assumption of known detection probability. This assumption can lead to biased or even complete corruption of estimation results. This paper proposes a method for tracking multiple targets from multistatic Doppler radar with unknown detection probability. A closed form labeled multitarget Bayes filter was used to track unknown and time-varying targets with unknown probability of detection in the presence of clutter, misdetection, and association uncertainty. The efficiency of the proposed algorithm was illustrated via numerical simulation examples.

Scalable Adaptive Multitarget Tracking Using Multiple Sensors

2016 ◽  
Author(s):  
Florian Meyer ◽  
Paolo Braca ◽  
Franz Hlawatsch ◽  
Michele Micheli ◽  
Kevin D. LePage
Keyword(s):  
Multitarget Tracking ◽  
Multiple Sensors

Numerical Study on Hydrodynamic Responses of a Two-Body System in Side-by-Side Operation

2016 ◽  
Author(s):  
Shaowu Ou ◽  
Shixiao Fu ◽  
Wei Wei ◽  
Tao Peng ◽  
Xuefeng Wang
Keyword(s):  
Numerical Study ◽  
Low Frequency ◽  
Optimal Operation ◽  
Hydrodynamic Interactions ◽  
Irregular Waves ◽  
Mooring System ◽  
Time Varying ◽  
Body System ◽  
The Time Domain ◽  
Two Bodies

Typically, in some side-by-side offshore operations, the speed of vessels is very low or even 0 and the headings are manually maneuvered. In this paper, the hydrodynamic responses of a two-body system in such operations under irregular seas are investigated. The numerical model includes two identical PSVs (Platform Supply Vessel) as well as the fenders and connection lines between them. A horizontal mooring system constraining the low frequency motions is set on one of the ships to simulate maneuver system. Accounting for the hydrodynamic interactions between two bodies, 3D potential theory is applied for the analysis of their hydrodynamic coefficients. With wind and current effects included, these coefficients are further applied in the time domain simulations in irregular waves. The relevant coefficients are estimated by experiential formulas. Time-varying loads on fenders and connection lines are analyzed. Meanwhile, the relative motions as well as the effects of the hydrodynamic interactions between ships are further discussed, and finally an optimal operation scheme in which operation can be safely performed is summarized.

scholarly journals Joint Tracking and Classification of Extended Targets Using Random Matrix and Bernoulli Filter for Time-Varying Scenarios

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 129584-129603 ◽  
Author(s):  
Liping Wang ◽  
Yuan Huang ◽  
Ronghui Zhan ◽  
Jun Zhang
Keyword(s):  
Random Matrix ◽  
Time Varying ◽  
Bernoulli Filter ◽  
Joint Tracking

scholarly journals Distributed Multiagent Control Approach for Multitarget Tracking

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Liang Ma ◽  
Kai Xue ◽  
Ping Wang
Keyword(s):  
Information Fusion ◽  
Multitarget Tracking ◽  
Control Approach ◽  
Numerical Studies ◽  
Utility Optimization ◽  
Partially Observed ◽  
Markov Decision ◽  
Multiagent Control ◽  
Bernoulli Filter ◽  
Effectiveness And Efficiency

In multiagent systems, tracking multiple targets is challenging for two reasons: firstly, it is nontrivial to dynamically deploy networked agents of different types for utility optimization; secondly, information fusion for multitarget tracking is difficult in the presence of uncertainties, such as data association, noise, and clutter. In this paper, we present a novel control approach in distributed manner for multitarget tracking. The control problem is modelled as a partially observed Markov decision process, which is a NP-hard combinatorial optimization problem, by seeking all possible combinations of control commands. To solve this problem efficiently, we assume that the measurement of each agent is independent of other agents’ behavior and provide a suboptimal multiagent control solution by maximizing the local Rényi divergence. In addition, we also provide the SMC implementation of the sequential multi-Bernoulli filter so that each agent can utilize the measurements from neighbouring agents to perform information fusion for accurate multitarget tracking. Numerical studies validate the effectiveness and efficiency of our multiagent control approach for multitarget tracking.

Efficient uncertainty propagation for MAPOD via polynomial chaos-based Kriging

2019 ◽  
Vol 37 (1) ◽  
pp. 73-92 ◽  
Author(s):  
Xiaosong Du ◽  
Leifur Leifsson
Keyword(s):  
Polynomial Chaos ◽  
State Of The Art ◽  
Uncertainty Propagation ◽  
Kriging Model ◽  
Probability Of Detection ◽  
Kriging Interpolation ◽  
Benchmark Problems ◽  
Content Type ◽  
Order Of Magnitude ◽  
Polynomial Chaos Expansions

Purpose Model-assisted probability of detection (MAPOD) is an important approach used as part of assessing the reliability of nondestructive testing systems. The purpose of this paper is to apply the polynomial chaos-based Kriging (PCK) metamodeling method to MAPOD for the first time to enable efficient uncertainty propagation, which is currently a major bottleneck when using accurate physics-based models. Design/methodology/approach In this paper, the state-of-the-art Kriging, polynomial chaos expansions (PCE) and PCK are applied to “a^ vs a”-based MAPOD of ultrasonic testing (UT) benchmark problems. In particular, Kriging interpolation matches the observations well, while PCE is capable of capturing the global trend accurately. The proposed UP approach for MAPOD using PCK adopts the PCE bases as the trend function of the universal Kriging model, aiming at combining advantages of both metamodels. Findings To reach a pre-set accuracy threshold, the PCK method requires 50 per cent fewer training points than the PCE method, and around one order of magnitude fewer than Kriging for the test cases considered. The relative differences on the key MAPOD metrics compared with those from the physics-based models are controlled within 1 per cent. Originality/value The contributions of this work are the first application of PCK metamodel for MAPOD analysis, the first comparison between PCK with the current state-of-the-art metamodels for MAPOD and new MAPOD results for the UT benchmark cases.

Electrostatic Aberration Correction in LV-SEM

2000 ◽  
Vol 6 (S2) ◽  
pp. 746-747 ◽  
Author(s):  
D.J. Maas ◽  
A. Henstra ◽  
M.P.C.M. Krijn ◽  
S.A.M. Mentink
Keyword(s):  
Electron Microscope ◽  
Low Voltage ◽  
State Of The Art ◽  
Spherical Aberration ◽  
Positive Definite ◽  
Ease Of Use ◽  
Objective Lens ◽  
Time Varying ◽  
Voltage Electron ◽  
Aberration Corrected

The resolution of a low-voltage electron microscope is limited by the chromatic and spherical aberration of the objective lens, see Fig. 1. The design of state-of-the-art objective lenses is optimised for minimal aberrations. Any significant improvement of the resolution requires an aberration corrector. Recently, correction of both Cc and Cs has been demonstrated in SEM, using a combination of magnetic and electrostatic quadrupoles and octupoles (Zach and Haider, 1995). The present paper presents an alternative design, which is based on a purely electrostatic concept, potentially simplifying the ease-of-use of an aberration corrected microscope.In 1936 Scherzer showed that the fundamental lens aberrations of round lenses are positive definite, in absence of time-varying fields and/or space charge. Negative lens aberrations, required for the correction of Cc and Cs, can only be obtained using non-round lenses, e.g. quadrupoles and octupoles (Scherzer, 1947).

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