Optimal deployment of multistatic radar for belt barrier coverage

Li, Haipeng; Feng, Da‐Zheng; Liu, Chao; Zhang, Chi

doi:10.1007/s11276-022-02939-5

Cited by 4 publications

(4 citation statements)

References 38 publications

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“…The latter patterns are then used through an Integer Linear Program (ILP) and an exhaustive method to address the global problem. Li et al (Li et al, 2022) propose an ILP and exhaustive search to determine multiple unequal-width barrier coverages of the AoI (with different deployment sequences).…”

Section: Literature Reviewmentioning

confidence: 99%

An improved two-phase heuristic for active multistatic sonar network configuration

Thuillier,

Le Josse,

Olteanu

et al. 2024

Expert Systems with Applications

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Section: Literature Reviewmentioning

confidence: 99%

An improved two-phase heuristic for active multistatic sonar network configuration

Thuillier,

Le Josse,

Olteanu

et al. 2024

Expert Systems with Applications

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“…In [13], Chang et al adopted the minimum deployment cost criterion to construct the belt barrier coverage and integrated the sensor fault tolerance and energy saving into the deployment problem. In [14], Gong et al considered an MRN to minimize the vulnerability of the barrier and study the optimal deployment of MRs on a line segment to minimize its vulnerability. In [15−17], a belt barrier coverage along a line was built to minimize the total placement cost.…”

Section: Introductionmentioning

confidence: 99%

“…In [15−17], a belt barrier coverage along a line was built to minimize the total placement cost. Chen et al [18] and Li et al [19] focused on the perimeter barrier coverage problem and optimally deployed MRs to achieve minimum deployment cost. Xu et al [20] and Li et al [21] adopted MRs to build the circular barrier coverage with a certain width.…”

Section: Introductionmentioning

confidence: 99%

Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

Feng

2023

J. of Syst. Eng. Electron.

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This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions. This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence. Based on these properties and considering location restrictions, it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars. To overcome the nonconvexity of the model and the non-analytical nature of the objective function, an algorithm combining integer line programming and the cuckoo search algorithm (CSA) is proposed. The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost. Simulations are conducted in different conditions to verify the effectiveness of the proposed method.

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“…A radar deployment problem was translated into a graph theory problem by some preprocessing operations, like discretization, to solve a multiobjective optimization problem for radar deployment based on graph theory knowledge [5]. An optimal placement method about perimeter barrier coverage was introduced to solve the optimal placement issue for multistatic radar on the perimeter curve [6]. In view of existing problems in the deployment of tra c surveillance radars in civil aviation, an adaptive genetic algorithm with elite selection strategies was proposed to optimize the deployment of surveillance radars [7].…”

Section: Introductionmentioning

confidence: 99%

The Opposition-Based Learning Parameter Adjusting Harmony Search Algorithm Research on Radars Optimal Deployment

Cui

Dong

et al. 2022

Mathematical Problems in Engineering

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In order to solve the problem of maximizing the utilization of resources through reasonable deployment under limited resources, this paper studies from two aspects: one is to establish the mathematical model of maximum coverage of space detection, and the other is to improve the harmony algorithm. The exploration performance and convergence performance of the harmony search algorithm are analyzed theoretically, and the more general formulas of exploration performance and convergence performance are proved. Based on theoretical analysis, the algorithm called opposition-based learning parameter adjusting harmony search is proposed. By using the algorithm to test the functions of different properties, the value range of key control parameters of the algorithm are given. The proposed algorithm is applied to optimize the problem of radar deployment. This paper takes a certain area of the Shandong Peninsula as the deployment scope. The simulation results show that the proposed algorithm is effective and practical. Although there is a large amount of calculation, it provides ideas and ways for other problems, such as the site selection of new observation and communication post, the deployment of maneuvering radar stations, and the track planning of fleet.

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Optimal deployment of multistatic radar for belt barrier coverage

Cited by 4 publications

References 38 publications

An improved two-phase heuristic for active multistatic sonar network configuration

An improved two-phase heuristic for active multistatic sonar network configuration

Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

The Opposition-Based Learning Parameter Adjusting Harmony Search Algorithm Research on Radars Optimal Deployment

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