Clustered Mixture Particle Filter for Underwater Multitarget Tracking in Multistatic Active Sonobuoy Systems

Georgy, Jacques; Noureldin, Aboelmagd; Mellema, Garfield R.

doi:10.1109/tsmcc.2011.2154329

Cited by 26 publications

(12 citation statements)

References 32 publications

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“…An evidence theorybased framework is utilized to determine the structure of the global posterior distribution. In [8,9], an enhanced version of PF is employed and is called Mixture PF, which samples from both the prior and the observation likelihood, as compared to the majority of PF variants that sample from only a single importance density. In order to be able to track an unknown time varying number of multiple targets, two Mixture PFs are used, one for target detection and the other for tracking multiple targets, and a density-based clustering technique is used after the first filter.…”

Section: ) Particle Filteringmentioning

confidence: 99%

“…The visible and IR camera MTT systems have been used in the applications of ballistic missile guidance [5] and space-based early warning [6], which are required to identify and track several hundred targets in real time [7]. For underwater target tracking, sonar MTT systems are deployed on an airplane or ship, and submerged for monitoring the underwater acoustics [8,9].…”

Section: Introductionmentioning

confidence: 99%

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A Survey of Motion-Based Multitarget Tracking Methods

Qiu¹,

Zhang²,

Lü³

et al. 2015

PIER B

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Abstract-Multitarget tracking (MTT) in surveillance system is extremely challenging, due to uncertain data association, maneuverable target motion, dense clutter disturbance, and real-time processing requirements. A good many methods have been proposed to cope with these challenges. However, no up-to-date survey is available in the literature that can help to select suitable tracking algorithm for practical problem. This paper provides a comprehensive review of the state-of-the-art motion-based MTT techniques, classifies existing methods into two groups, i.e., the detect-beforetrack (DBT) scheme and the track-before-detect (TBD) scheme. The DBT scheme is employed to achieve robust and tractable tracking performance when the signal-noise-ratio (SNR) is strong. The TBD scheme is used in the scenarios of low SNR, and it aims to cumulate target energy by multiple sensor frames. Furthermore, depending on the data association mechanism, the DBT methods can be classified into two categories, data association based approaches and finite set statistics (FISST) based approaches. And the TBD methods can be classified into non-Bayesian approaches and Bayesian approaches depending on the basis theory used for tracking. For each category, this paper provides the detailed descriptions of the representative algorithms, and examines their pros and cons. Finally, new trends for future research directions are offered.

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Section: ) Particle Filteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey of Motion-Based Multitarget Tracking Methods

Qiu¹,

Zhang²,

Lü³

et al. 2015

PIER B

View full text Add to dashboard Cite

show abstract

“…In recent years, underwater wireless sensor networks (UWSNs) have gradually become an important technology for human beings to explore and utilize underwater resources. As an extension of terrestrial wireless sensor networks, UWSNs can be used for disaster warning, environmental monitoring, underwater target detection and tracking [1,2,3,4,5]. In this paper, we focus on the problem of underwater target tracking using UWSNs.…”

Section: Introductionmentioning

confidence: 99%

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Liu

Zhang

et al. 2017

Sensors

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Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

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“…Despite the advantages of multistatic sonar tracking systems, their use is challenging because of the complexity of the underwater environment. The underwater environment is time varying and spare varying, characterized by low target detection probability and an extremely large number of false alarms caused by reverberation [ 2 , 3 ]. Meanwhile, the low speed of acoustic propagation might result in measurement time delay, which will increase uncertainty in target location.…”

Section: Introductionmentioning

confidence: 99%

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter

et al. 2015

Sensors

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Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

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Clustered Mixture Particle Filter for Underwater Multitarget Tracking in Multistatic Active Sonobuoy Systems

Cited by 26 publications

References 32 publications

A Survey of Motion-Based Multitarget Tracking Methods

A Survey of Motion-Based Multitarget Tracking Methods

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter

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