Heterogeneous Multiple Sensors Joint Tracking of Maneuvering Target in Clutter

Wu, Panlong; Li, Xingxiu; Kong, Jian; Liu, Jiale

doi:10.3390/s150717350

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…Also, measurement vector and the Jacobian of measurement vector for each association event can be defined as equations (33) and (34), respectively. In equation 34, C 1 k is the Jacobian of f 1 ðx k Þ "…”

Section: Current State Predictionmentioning

confidence: 99%

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Multi-sensor target tracking in the presence of clutter using game theory

Ghazal

Doustmohammadi

2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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The problem of multi-sensor target tracking in the presence of clutter has not been studied from a game theory point of view. This paper presents a game theory approach for such a problem. Fundamental sub-problems are state estimation and data association in multi-sensor target tracking systems. In this paper, the state estimation problem is formulated as zero-sum game and a minimax filter is developed to estimate the target characteristics, including its position, velocity, and acceleration. To extend the filter in the presence of clutter, a data association framework is proposed. In data association framework, set of new hypotheses in each step is produced from set of validated measurements and the ith global hypothesis is obtained from the previous step. Next, posteriori estimate of ith global hypothesis is updated based on the filter for each new hypothesis. To manage exponential growth of new hypotheses, a new k-best algorithm is implemented. Simulation results illustrate the improved performance of the proposed filter compared to multiple hypothesis tracking and nearest-neighbor fuzzy filters.

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Section: Current State Predictionmentioning

confidence: 99%

“…Nowadays, radar/IR tracking system is interesting to researchers due to its flexibility, redundancy, simplicity, and reliability. 1 The radar is an active sensor that uses radio waves to determine range and azimuth angles of the target. However, it is easy to be interfered by electromagnetic signals.…”

Section: Introductionmentioning

confidence: 99%

Multi-sensor target tracking in the presence of clutter using game theory

Ghazal

Doustmohammadi

2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…Different from the single sensor node tracking system, multiple sensor node collaborative network employs a local fusion center to collect data from nearby nodes and to conduct estimation on target state. 8,9 Obviously, the robustness of tracking accuracy will be improved in this network but with excessive energy consumption. In massive literatures, [10][11][12] a lot of attempts are given to resolve this contradiction between tracking accuracy and network lifespan.…”

Section: Introductionmentioning

confidence: 99%

An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks

Tang

Cheng

et al. 2017

International Journal of Distributed Sensor Networks

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Improving tracking quality and extending network lifespan are two main objects for target tracking, which are usually contradictory due to limited energy of sensor nodes in wireless sensor networks. This article incorporates this contradiction into a problem of multi-objective optimization in tracking networks where multiple sensor nodes are scheduled for collaborative target tracking by adopting the unscented Kalman filter algorithm. We propose an effective scheme to extend the lifespan of wireless sensor networks while guaranteeing preset tracking quality. More specifically, with regard to practical circumstances, we perform analysis on the target detection probability, as well as residual energy of sensor nodes, when selecting a suitable set of candidate sensor nodes. Then, we put forward a novel energy-balanced sensor nodes scheduling algorithm, Greedy Balance Replace Heuristic Algorithm, to select a near-optimal task sensor set from the candidate sensor node set to balance tracking quality and network lifetime. In addition, we also design an efficient multi-sensor node collaborative method to track a single target and to timely report its state to the remote end. From simulation results, it is demonstrated that the proposed node scheduling scheme can not only maintain the preset tracking accuracy but also extend network lifespan with a low computation complexity.

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“…Keeping the cost and size of these sensors small, they are equipped with low computation capability, small amounts of memory, and limited energy resources. Wireless sensor networks (WSN) must rely on these sensors and collaborative signal processing to dynamically manage node resources and effectively process distributed information [5,6,7]. Along this direction, moving target tracking will be considered in WSN.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Moving Target Tracking in Wireless Sensor Networks

Wen

Gao

Zhao

2016

Sensors

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Moving target tracking in wireless sensor networks is of paramount importance. This paper considers the problem of state estimation for L-sensor linear dynamic systems. Firstly, the paper establishes the fuzzy model for measurement condition estimation. Then, Generalized Kalman Filter design is performed to incorporate the novel neighborhood function and the target motion information, improving with an increasing number of active sensors. The proposed measurement selection approach has some advantages in time cost. As such, if the desired accuracy has been achieved, the parameter initialization for optimization can be readily resolved, which maximizes the expected lifespan while preserving tracking accuracy. Through theoretical justifications and empirical studies, we demonstrate that the proposed scheme achieves substantially superior performances over conventional methods in terms of moving target tracking under the resource-constrained wireless sensor networks.

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Heterogeneous Multiple Sensors Joint Tracking of Maneuvering Target in Clutter

Cited by 10 publications

References 14 publications

Multi-sensor target tracking in the presence of clutter using game theory

Multi-sensor target tracking in the presence of clutter using game theory

An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks

Energy Efficient Moving Target Tracking in Wireless Sensor Networks

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