<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To address the problem of inaccurate positioning of new energy vehicles during cooperative detection, this paper investigates the positioning accuracy of different combinations of radar and infrared sensors. In order to meet the control requirements of the vehicle co-detection formation, a distributed control method considering the vehicle dynamics characteristics is adopted for this purpose. And considering the cost of sensors, the optimal parameters are calculated, and an optimal aircraft co-detection configuration design scheme based on the SCP model (structure-behavior-performance model) is proposed. At the working level of multi-craft cooperative detection guidance, a two-layer cooperative guidance structure is designed based on the basic framework. Research on vehicle configuration design, vehicle data transmission, processing technology, and cooperative detection and guidance is carried out. The basic principles of the particle swarm optimization algorithm and the algorithmic flow of the discrete particle swarm algorithm are applied to calculate the assignment of targets by the particle swarm optimization algorithm. The GDOP values are analyzed according to the simulation results, and it can be concluded that: the change rate of 2~5 sensors accuracy can reach 71.1%, 71.6%, and 71.5%, respectively, when the infrared sensor spacing is 1km~3km. 5~10 sensors accuracy change rate is only 53.3%, 52.2%, and 49.7%, respectively, which shows that the value is improved by 20%, indicating that the collaborative sensing accuracy of the aircraft has been effectively improved, which is of great help to the collaborative detection of new energy vehicles based on SCP model.</p>
</abstract>

To address the problem of inaccurate positioning of new energy vehicles during cooperative detection, this paper investigates the positioning accuracy of different combinations of radar and infrared sensors. In order to meet the control requirements of the vehicle co-detection formation, a distributed control method considering the vehicle dynamics characteristics is adopted for this purpose. And considering the cost of sensors, the optimal parameters are calculated, and an optimal aircraft co-detection configuration design scheme based on the SCP model (structure-behavior-performance model) is proposed. At the working level of multi-craft cooperative detection guidance, a two-layer cooperative guidance structure is designed based on the basic framework. Research on vehicle configuration design, vehicle data transmission, processing technology, and cooperative detection and guidance is carried out. The basic principles of the particle swarm optimization algorithm and the algorithmic flow of the discrete particle swarm algorithm are applied to calculate the assignment of targets by the particle swarm optimization algorithm. The GDOP values are analyzed according to the simulation results, and it can be concluded that: the change rate of 2~5 sensors accuracy can reach 71.1%, 71.6%, and 71.5%, respectively, when the infrared sensor spacing is 1km~3km. 5~10 sensors accuracy change rate is only 53.3%, 52.2%, and 49.7%, respectively, which shows that the value is improved by 20%, indicating that the collaborative sensing accuracy of the aircraft has been effectively improved, which is of great help to the collaborative detection of new energy vehicles based on SCP model.

SCP model based on the new energy vehicle collaborative detection configuration method research

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

To address the problem of inaccurate positioning of new energy vehicles during cooperative detection, this paper investigates the positioning accuracy of...

SCP model based on the new energy vehicle collaborative detection configuration method research

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: -

Eingereicht: 17. Mai 2022

Akzeptiert: 28. Sept. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00113

Schlüsselwörter
SCP model, Particle swarm optimization algorithm, Radar and infrared sensor, Cooperative vehicle detection configuration, Two-layer cooperative guidance

© 2023 Mingyang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

SCP model based on the new energy vehicle collaborative detection configuration method research

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: -

Eingereicht: 17. Mai 2022

Akzeptiert: 28. Sept. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00113

SchlüsselwörterSCP model, Particle swarm optimization algorithm, Radar and infrared sensor, Cooperative vehicle detection configuration, Two-layer cooperative guidance

© 2023 Mingyang Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
SCP model, Particle swarm optimization algorithm, Radar and infrared sensor, Cooperative vehicle detection configuration, Two-layer cooperative guidance