Timeliness Constrained Task Scheduling for Multifunction Radar Network

Tian, Tuanwei; Zhang, Tianxian; Kong, Lingjiang

doi:10.1109/jsen.2018.2878795

Cited by 25 publications

(10 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the imaging task is time sensitive that if imaging start moment is different, the imaging time is different. In a case when the azimuth resolution is given and the imaging start moment is chosen, the rotation angle can be calculated by (5), the imaging time can be obtained by (9).…”

Section: B Imaging Time Under Required Image Qualitymentioning

confidence: 99%

“…Yan et al proposed a joint threshold adjustment and power allocation algorithm for target tracking in asynchronous radar network [8]. Furthermore, Tian et al proposed a timeliness constrained task scheduling algorithm to solve the multifunction radar network task scheduling problem and the numerical results verify the validity of the proposed task scheduling algorithm [9]. However, these studies focus on the multi-target detection, tracking, location scheme, estimation of the target characteristics, while there are few researches on the optimization of imaging task scheduling problem in radar network.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Task Scheduling for Multi-Target ISAR Imaging in Radar Network

et al. 2020

View full text Add to dashboard Cite

For radar imaging of multiple targets in radar network, it is necessary to schedule the imaging tasks among various radars at suitable time to achieve high performance under limited radar resources. In this paper, based on the image quality requirement, a task schedule method is proposed for multi-target inverse synthetic aperture radar (ISAR) imaging in radar network. Due to the image resolution is an important indicator of image quality and the imaging task is time sensitive, the relationship between the imaging resolution and task time is studied firstly. Thereafter, the task scheduling problem is converted into an optimization problem with time window constrains and an improved Quantum Genetic Algorithm (IQGA) is proposed to solve the problem. Then the task scheduling strategy which contains how to allocate the targets to the radars and when to observe the targets can be obtained. Finally, simulation results verify the effectiveness of the proposed method. With the help of the propose method, the multi-target ISAR task can be completed effectively and the resource utilization of the radar network can be improved. INDEX TERMS Radar network, multi-target imaging, task scheduling optimization, time window, improved quantum genetic algorithm (IQGA).

show abstract

Section: B Imaging Time Under Required Image Qualitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Task Scheduling for Multi-Target ISAR Imaging in Radar Network

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Yan et al 10 proposed an optimal antenna deployment algorithm for the problem of multiregion simultaneous interference. Furthermore, Tian et al 11 proposed a time-constrained task scheduling algorithm for a multifunctional radar network task scheduling problem and verified the effectiveness of the algorithm. These studies all focus on resource scheduling for target detection, tracking, location, and target feature cognition.…”

Section: Introductionmentioning

confidence: 98%

Resource scheduling algorithm optimization for multitarget inverse synthetic aperture radar imaging in radar network

Wang

Liao

Ouyang

et al. 2021

J. Appl. Rem. Sens.

View full text Add to dashboard Cite

Aiming at optimizing the allocation problem of limited resources in a radar network, a resource scheduling algorithm combining pulse interleaving with preallocation is proposed for multitarget inverse synthetic aperture radar imaging. The imaging method adopts compressed sensing, which only needs to emit a small number of pulses so that we can set the algorithms to schedule the allocation of the pulses over a period of time. The authors point out the problem of pulse conflict, which is ignored in the process of the scheduling algorithm and proposes a preallocation method to avoid the occurrence of the conflict. Meanwhile, pulse interleaving is added to increase the positions of the dispatchable pulses. Moreover, the combined algorithm can perform adaptive scheduling on the radar time resource according to the feature parameters after target feature cognitive. Finally, the feasibility of the combined algorithm is verified by the simulation, and two performance indicators, the hit value rate and the pulse utilization rate, are improved by the proposed algorithm. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

show abstract

“…Recent information battlefield scenarios urge modern radar equipment to deploy optimally [1,2] and exchange the estimation information [3] with each other. How to form an integrated system by combining the radar equipment with the communication equipment and solve the problems of the generalization, such as tremendous wireless data traffic, rational use of the system resources [4][5][6] has been the theme of increasing research over recent years. Spectrum sharing between radar and communication systems, which can overcome the shortage of spectrum resources and improve the efficiency of the spectrum significantly, is one of the essential research studies and has been a hot topic [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Data Transmission for Joint Radar and Communication Systems

Tian

Tang

et al. 2021

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

This paper investigates the problem of data transmission for the joint radar and communication systems (JRCSs). The performance of the JRCS is characterized by data throughput related to the radar echo data (RED) and communication data rate (CDR). Two spectral coexistence schemes are proposed based on the degree of spectrum sharing for radar and communication, i.e., the isolated subfrequency band (ISFB) and mix-used frequency band (MUFB) schemes. Firstly, the signals of radar and communication are operated on the isolated subcarriers, enabling the received signals to be processed independently and bringing the advantage of interference avoidance. Secondly, the signals of radar and communication can be jointly operated on the same subcarriers for the MUFB scheme, which enhances the spectrum efficiency. Unlike the ISFB scheme, the CDR of the MUFB scheme is maximized along with the interference from the radar signal, and meanwhile, the allocated radar power on each subcarrier is derived by maximizing the radar mutual information. Numerical results show that the MUFB scheme significantly improves the performance of data transmission over the ISFB scheme, and a significant performance gain in the data transmission can be achieved, compared to the average power allocation case.

show abstract

Timeliness Constrained Task Scheduling for Multifunction Radar Network

Cited by 25 publications

References 32 publications

Task Scheduling for Multi-Target ISAR Imaging in Radar Network

Task Scheduling for Multi-Target ISAR Imaging in Radar Network

Resource scheduling algorithm optimization for multitarget inverse synthetic aperture radar imaging in radar network

Performance Analysis of Data Transmission for Joint Radar and Communication Systems

Contact Info

Product

Resources

About